Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-10-18 17:28 UTC

ai-forever / gigachat

GigaChat API access library

PythonMIT★ 171 stars⑂ 45 forkssince Sep 2023View on GitHub ↗
KindLibraryhow this is determined
#ai#llm#gigachain#gigachat

ai-forever/gigachat holds a health index of 34 out of 100, placing it in the At Risk band. It scores highest on AI Readiness (86/100) and lowest on Security (31/100). It was last updated 9 days ago. 2 contributors account for most of its recent work.

34
overall / 100
At Risk

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.

34
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 68 is calibrated to 80 on the published index scale (record calibration 2026-08-02). High-Risk Jurisdiction Policy applies a 50% multiplier to weighted overall health and gives it an At Risk ceiling of 34.

Ownership

AI ForeverOrganization
1,240 followers127 public repossince Apr 2022

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIgigachat0.2.3249,3685979 days ago

Metrics by category

Vitality

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

76Good · 21% of overall

Development activity

60Moderate
How it's scored
28.8/36Push recency — last push 9 days ago
11.1/36Commit cadence — 16/52 weeks with commits
16.8/18Commit volume — 73 commits in the last year
3/10OpenSSF Scorecard: Maintained — 4 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 3
Inputs used
commits_last_year73
human_commit_share1
days_since_last_push9
active_weeks_last_year16

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 19 releases published
36/36Release recency — latest release 9 days ago
27/27Release cadence — a release every ~36.9 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count19
latest_release_tagv0.2.4a1
releases_from_tagsno
days_since_latest_release9
mean_days_between_releases36.9
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?

72Good · 17% of overall

Popularity & adoption

56Moderate
How it's scored
36.2/60Stars — 171 stars
13.7/25Forks — 45 forks
6.2/15Watchers — 14 watchers
Inputs used
forks45
stars171
watchers14
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

77Good
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
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges4
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_servicesshields.io
has_pull_request_templateyes

Ecosystem adoption (downloads)

90Excellent
How it's scored
72/80Monthly downloads — 249,368 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesgigachat
dependents—
ecosystemspypi
total_downloads—
monthly_downloads249,368
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?

73Good · 23% of overall

Maintainer resilience (bus factor)

58Moderate
How it's scored
25.2/54Bus factor — 2 contributor(s) cover half of all commits
16.2/22.5Commit distribution — top contributor authored 28% of commits
13.5/13.5Contributor breadth — 13 contributors
3/10OpenSSF Scorecard: Contributors — project has 1 contributing companies or organizations -- score normalized to 3
Inputs used
bus_factor2
contributors_sampled13
top_contributor_share0.278

Issue & PR responsiveness

70Good
How it's scored
32/42Issue resolution — 76% of issues closed
24.4/30PR acceptance — 79/97 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
4.5/15OpenSSF Scorecard: Code-Review — Found 3/8 approved changesets -- score normalized to 3
Inputs used
merged_prs79
open_issues5
closed_issues16
prs_merged_7d0
prs_decided_7d0
prs_merged_30d2
prs_decided_30d2
issue_closed_ratio0.762
closed_unmerged_prs18
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.

Ownership & stewardship

74Good
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
22.2/25Owner reach — 1,240 followers of ai-forever
22/25Track record — 127 public repos, account ~4 yr old
Inputs used
followers1,240
owner_typeOrganization
is_verifiedno
owner_loginai-forever
public_repos127
account_age_days1,649

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 79 days ago
20/20Version history — 59 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesgigachat
ecosystemspypi
any_deprecatedno
min_days_since_publish79

Engineering Quality

Are baseline engineering and documentation practices in place?

78Good · 19% of overall

Engineering practices

90Excellent
How it's scored
24/24CI workflows — 1 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff])
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
16/20OpenSSF Scorecard: CI-Tests — 6 out of 7 merged PRs checked by a CI test -- score normalized to 8
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

60Moderate
How it's scored
30/30README
0/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
10/10Topics — 4 topics
10/10Wiki
Inputs used
topicsai, llm, gigachain, gigachat
has_wikiyes
homepage—
docs_site—
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

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

31At Risk · 16% of overall

Security posture

14Critical
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — branch protection not enabled on development/release branches
2/2.5CI-Tests — 6 out of 7 merged PRs checked by a CI test -- score normalized to 8
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
2.2/7.5Code-Review — Found 3/8 approved changesets -- score normalized to 3
0.8/2.5Contributors — project has 1 contributing companies or organizations -- score normalized to 3
10/10Dangerous-Workflow — no dangerous workflow patterns detected
0/7.5Dependency-Update-Tool — no update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
2.2/7.5Maintained — 4 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 3
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 — 23 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate2.9
high_risk_jurisdiction_cap34
high_risk_jurisdiction_multiplier50
security_posture_after_multiplier14
security_posture_before_jurisdiction29
Excluded from scoring (no data or not applicable): Packaging, Signed-Releases. Remaining weights renormalized. High-Risk Jurisdiction Policy applies a 50% multiplier and gives Security posture an At risk ceiling of 34.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisories — no direct dependency carries a known advisory
25/25Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
0/40No advisories left outstanding — no advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages13
unassessed_packages0
affected_by_severitynone
direct_affected_packages0
Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:gigachat@0.2.3 runtime dependency closure — what installing the published package pulls in — 13 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.

86Excellent · 4% of overall

Agent context & guidance

85Excellent
How it's scored
45/45Agent instructions — AGENTS.md, CLAUDE.md
0/15Machine-readable docs (llms.txt)
40/40Legible commit history — 93 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.93
agent_instruction_filesAGENTS.md, CLAUDE.md
agent_instruction_max_bytes4,223

Verify loop (build / test / typecheck)

82Excellent
How it's scored
18/18One-command bootstrap — Makefile
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff])
11/11Static type checking — src/gigachat/py.typed
10/10Reproducible environment — lockfile
10/10Demonstrated agent practice — 6 of the last 100 commits agent-authored or agent-credited
0/8Automated maintenance — no automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileno
typed_languageno
bootstrap_filesMakefile
has_devcontainerno
has_linter_configyes
typecheck_configssrc/gigachat/py.typed
agent_commit_share0.06
toolchain_manifests—
dependency_bot_commit_share0

Code legibility for models

82Excellent
How it's scored
27/45Type-checkable code — Python with type-check config (src/gigachat/py.typed)
54.5/55Manageable file sizes — 1/122 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes62,818
source_files_sampled122
oversized_source_files1

Machine-readable interfaces

100Exceptional
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

171GitHub stars
13contributors
73commits, last 12 months
9days since last push
19releases
2bus factor
5open issues
PyPIpackage ecosystems

Data collection warnings

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

More detail

Star and fork history 0 ★ / 45 ⇿
0Stars
45Forks
18Releases

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.

010203040504532023-102025-042026-09
Major 0Minor 1Patch 7

Each point covers 3 days.

OpenSSF Scorecard 2.9 / 10
2.9aggregate

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 · 2026-10-18 17:28 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
8CI-Tests6 out of 7 merged PRs checked by a CI test -- score normalized to 8
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
3Code-ReviewFound 3/8 approved changesets -- score normalized to 3
3Contributorsproject has 1 contributing companies or organizations -- score normalized to 3
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
3Maintained4 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 3
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
0Vulnerabilities23 existing vulnerabilities detected
Direct dependencies 5
RegistryPackageVersion constraintManifest
PyPIpydantic>=2.0,<3pyproject.toml
PyPIpydantic-settings>=2.0,<2.9.0pyproject.toml
PyPIpydantic-settings>=2.0,<2.12.0pyproject.toml
PyPIpydantic-settings>=2.0,<3pyproject.toml
PyPIhttpx>=0.24,<1pyproject.toml
All dependencies 77

Full resolved dependency set from the GitHub dependency graph: 7 direct and 70 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIhttpx0.24.1direct
PyPIhttpx0.25.2direct
PyPIpydantic2.10.6direct
PyPIpydantic2.12.5direct
PyPIpydantic-settings2.11.0direct
PyPIpydantic-settings2.12.0direct
PyPIpydantic-settings2.8.1direct
PyPIannotated-types0.7.0indirect
PyPIanyio3.7.1indirect
PyPIcertifi2025.11.12indirect
PyPIcfgv3.4.0indirect
PyPIcfgv3.5.0indirect
PyPIcolorama0.4.6indirect
PyPIcoverage7.10.7indirect
PyPIcoverage7.13.0indirect
PyPIcoverage7.6.1indirect
PyPIdistlib0.4.0indirect
PyPIexceptiongroup1.3.1indirect
PyPIfilelock3.16.1indirect
PyPIfilelock3.19.1indirect
PyPIfilelock3.20.1indirect
PyPIgigachat0.2.4a1indirect
PyPIh110.14.0indirect
PyPIh110.16.0indirect
PyPIhttpcore0.17.3indirect
PyPIhttpcore1.0.9indirect
PyPIidentify2.6.1indirect
PyPIidentify2.6.15indirect
PyPIidna3.11indirect
PyPIiniconfig2.1.0indirect
PyPIiniconfig2.3.0indirect
PyPIlibrt0.7.4indirect
PyPImultidict6.1.0indirect
PyPImultidict6.7.0indirect
PyPImypy1.14.1indirect
PyPImypy1.19.1indirect
PyPImypy-extensions1.1.0indirect
PyPInodeenv1.9.1indirect
PyPIpackaging25.0indirect
PyPIpathspec0.12.1indirect
PyPIplatformdirs4.3.6indirect
PyPIplatformdirs4.4.0indirect
PyPIplatformdirs4.5.1indirect
PyPIpluggy1.5.0indirect
PyPIpluggy1.6.0indirect
PyPIpre-commit3.5.0indirect
PyPIpre-commit4.3.0indirect
PyPIpre-commit4.5.0indirect
PyPIpropcache0.2.0indirect
PyPIpropcache0.4.1indirect
PyPIpydantic-core2.27.2indirect
PyPIpydantic-core2.41.5indirect
PyPIpytest7.4.4indirect
PyPIpytest-asyncio0.23.8indirect
PyPIpytest-cov5.0.0indirect
PyPIpytest-cov7.0.0indirect
PyPIpytest-httpx0.22.0indirect
PyPIpytest-httpx0.26.0indirect
PyPIpytest-recording0.13.2indirect
PyPIpytest-recording0.13.4indirect
PyPIpython-dotenv1.0.1indirect
PyPIpython-dotenv1.2.1indirect
PyPIpyyaml6.0.3indirect
PyPIruff0.14.9indirect
PyPIsniffio1.3.1indirect
PyPItomli2.3.0indirect
PyPItyping-extensions4.13.2indirect
PyPItyping-extensions4.15.0indirect
PyPItyping-inspection0.4.2indirect
PyPIurllib31.26.20indirect
PyPIvcrpy6.0.2indirect
PyPIvcrpy7.0.0indirect
PyPIvcrpy8.1.0indirect
PyPIvirtualenv20.35.4indirect
PyPIwrapt2.0.1indirect
PyPIyarl1.15.2indirect
PyPIyarl1.22.0indirect
Dependency advisories 0

Installing pypi:gigachat@0.2.3 pulls in 13 packages, direct and transitive: 0 carry known advisories, of which 0 are direct dependencies.

No known advisories affect the assessed dependencies.

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

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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.