Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-10 21:54 UTC

langchain-ai / langchain-aws

Build LangChain Applications on AWS

PythonMIT★ 347 stars⑂ 310 forkssince Mar 2024View on GitHub ↗
KindLibraryhow this is determined
#aws#generative-ai#langchain#langchain-python

langchain-ai/langchain-aws holds a health index of 94 out of 100, placing it in the Exceptional band. It scores highest on Vitality (95/100) and lowest on Security (69/100). It was last updated today. 3 contributors account for most of its recent work.

94
overall / 100
Exceptional

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.

94
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 80 is calibrated to 94 on the published index scale (record calibration 2026-08-02).

Ownership

LangChainOrganization
22,261 followers260 public repossince Mar 2023

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIlangchain-aws1.7.510,590,902898 days ago—
PyPIlanggraph-checkpoint-aws1.2.3-187 days agoawsbedrocklangchainlanggraphcheckpointerdynamodbelasticachevalkey
PyPIlangchain-agentcore-codeinterpreter0.0.559,023579 days agoagentcoreawsbedrockcode-interpreterdeepagentslangchainsandbox

Metrics by category

Vitality

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

95Exceptional · 21% of overall

Development activity

99Exceptional
How it's scored
36/36Push recency — last push 0 days ago
35.3/36Commit cadence — 51/52 weeks with commits
18/18Commit volume — 414 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 14 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year414
human_commit_share0.84
days_since_last_push0
active_weeks_last_year51

Release discipline

90Excellent
How it's scored
27/27Ships releases — 100 releases published
36/36Release recency — latest release 7 days ago
27/27Release cadence — a release every ~4.1 days
0/10OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases.
Inputs used
releases_count100
latest_release_taglanggraph-checkpoint-aws==1.2.3
releases_from_tagsno
days_since_latest_release7
mean_days_between_releases4.1

Community & Adoption

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

81Excellent · 17% of overall

Popularity & adoption

66Good
How it's scored
41.2/60Stars — 347 stars
20.8/25Forks — 310 forks
4.3/15Watchers — 7 watchers
Inputs used
forks310
stars347
watchers7
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

85Excellent
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (MIT)
18/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges0
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_services—
has_pull_request_templateno

Ecosystem adoption (downloads)

100Exceptional
How it's scored
80/80Monthly downloads — 10,649,925 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packageslangchain-aws, langgraph-checkpoint-aws, langchain-agentcore-codeinterpreter
dependents—
ecosystemspypi
total_downloads—
monthly_downloads10,649,925
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?

80Excellent · 23% of overall

Maintainer resilience (bus factor)

76Good
How it's scored
36/54Bus factor — 3 contributor(s) cover half of all commits
16.2/22.5Commit distribution — top contributor authored 28% of commits
13.5/13.5Contributor breadth — 98 contributors
10/10OpenSSF Scorecard: Contributors — project has 10 contributing companies or organizations
Inputs used
bus_factor3
contributors_sampled98
top_contributor_share0.28

Issue & PR responsiveness

75Good
How it's scored
35.5/42Issue resolution — 85% of issues closed
26.3/30PR acceptance — 722/823 decided PRs merged
9.8/13Newcomer PR acceptance — 3/4 first-time contributors' PRs merged in 30d
3/15OpenSSF Scorecard: Code-Review — Found 5/24 approved changesets -- score normalized to 2
Inputs used
merged_prs722
open_issues60
closed_issues330
prs_merged_7d7
prs_decided_7d9
prs_merged_30d41
prs_decided_30d45
issue_closed_ratio0.846
closed_unmerged_prs101
first_time_authors_30d4
first_time_prs_merged_30d3
first_time_prs_decided_30d4

Ownership & stewardship

75Good
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
25/25Owner reach — 22,261 followers of langchain-ai
20.1/25Track record — 260 public repos, account ~3 yr old
Inputs used
followers22,261
owner_typeOrganization
is_verifiedno
owner_loginlangchain-ai
public_repos260
account_age_days1,288

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 3 package(s) on pypi
35/35Publish recency — latest publish 7 days ago
20/20Version history — 89 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packageslangchain-aws, langgraph-checkpoint-aws, langchain-agentcore-codeinterpreter
ecosystemspypi
any_deprecatedno
min_days_since_publish7

Engineering Quality

Are baseline engineering and documentation practices in place?

70Good · 19% of overall

Engineering practices

84Excellent
How it's scored
24/24CI workflows — 11 workflow(s)
24/24Tests present
16/16Linter config — libs/agentcore-codeinterpreter/pyproject.toml ([tool.ruff]), libs/aws/pyproject.toml ([tool.ruff]), libs/langgraph-checkpoint-aws/pyproject.toml ([tool.ruff])
0/9.6Pre-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
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno

Documentation

50Moderate
How it's scored
30/30README
0/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
10/10Topics — 4 topics
0/10Wiki
Inputs used
topicsaws, generative-ai, langchain, langchain-python
has_wikino
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?

69Good · 16% of overall

Security posture

61Moderate
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — no data
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
1.5/7.5Code-Review — Found 5/24 approved changesets -- score normalized to 2
2.5/2.5Contributors — project has 10 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
7.5/7.5Maintained — 30 commit(s) and 14 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
1/5SAST — SAST tool is not run on all commits -- score normalized to 2
4.5/5Security-Policy — security policy file 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
Inputs used
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate6.1
Excluded from scoring (no data or not applicable): Branch-Protection. Remaining weights renormalized.

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_packages40
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:langchain-aws@1.7.5 runtime dependency closure — what installing the published package pulls in — 40 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.

90Excellent · 4% of overall

Agent context & guidance

100Exceptional
How it's scored
45/45Agent instructions — AGENTS.md, CLAUDE.md
15/15Machine-readable docs (llms.txt) — llms.txt present
40/40Legible commit history — 84 of 84 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtyes
llms_txt_url—
legible_history_share1
agent_instruction_filesAGENTS.md, CLAUDE.md
agent_instruction_max_bytes7,965

Verify loop (build / test / typecheck)

82Excellent
How it's scored
18/18One-command bootstrap — libs/agentcore-codeinterpreter/Makefile, libs/aws/Makefile, libs/langgraph-checkpoint-aws/Makefile
22/22Automated tests
11/11Lint / format config — libs/agentcore-codeinterpreter/pyproject.toml ([tool.ruff]), libs/aws/pyproject.toml ([tool.ruff]), libs/langgraph-checkpoint-aws/pyproject.toml ([tool.ruff])
11/11Static type checking — libs/aws/langchain_aws/py.typed
10/10Reproducible environment — lockfile
2/10Demonstrated agent practice — 1 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance — 2 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
lockfilesuv.lock
has_dockerfileno
typed_languageno
bootstrap_fileslibs/agentcore-codeinterpreter/Makefile, libs/aws/Makefile, libs/langgraph-checkpoint-aws/Makefile
has_devcontainerno
has_linter_configyes
typecheck_configslibs/aws/langchain_aws/py.typed
agent_commit_share0.01
toolchain_manifests—
dependency_bot_commit_share0.02

Code legibility for models

81Excellent
How it's scored
27/45Type-checkable code — Python with type-check config (libs/aws/langchain_aws/py.typed)
53.7/55Manageable file sizes — 7/293 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes270,342
source_files_sampled293
oversized_source_files7

Machine-readable interfaces

100Exceptional
How it's scored
0/40API schema (OpenAPI/GraphQL/proto) — not applicable to this kind of software
20/20MCP server
40/40Runnable examples — notebooks, samples
Inputs used
example_dirsnotebooks, samples
has_mcp_signalyes
api_schema_files—
interfaces_expected_of—
Excluded from scoring (no data or not applicable): API schema (OpenAPI/GraphQL/proto). Remaining weights renormalized.

Key facts

347GitHub stars
98contributors
414commits, last 12 months
0days since last push
100releases
3bus factor
60open issues
—package ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • First-time contributor figures cover 12 of 13 authors (cap 12)
  • pypi download statistics for 'langgraph-checkpoint-aws' unavailable this scan (stats endpoint failed after retries); adoption may be under-evidenced

More detail

Star and fork history 0 ★ / 310 ⇿
0Stars
310Forks
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.

012525037530762024-032025-062026-09
Major 0Minor 1Patch 21

Each point covers 3 days.

OpenSSF Scorecard 6.1 / 10
6.1aggregate

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 · 2026-09-10 21:54 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
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
2Code-ReviewFound 5/24 approved changesets -- score normalized to 2
10Contributorsproject has 10 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 14 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
2SASTSAST tool is not run on all commits -- score normalized to 2
9Security-Policysecurity policy file detected
0Signed-ReleasesProject has not signed or included provenance with any releases.
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 11
RegistryPackageVersion constraintManifest
PyPIdeepagents>=0.1.0libs/agentcore-codeinterpreter/pyproject.toml
PyPIbedrock-agentcore>=1.1.4libs/agentcore-codeinterpreter/pyproject.toml
PyPIboto3>=1.42.42libs/agentcore-codeinterpreter/pyproject.toml
PyPIlangchain-core>=1.6.0libs/aws/pyproject.toml
PyPIboto3>=1.43.64libs/aws/pyproject.toml
PyPIpydantic>=2.10.6,<3libs/aws/pyproject.toml
PyPInumpy>=1.0.0,<3libs/aws/pyproject.toml
PyPIlanggraph-checkpoint>=3.0.0,<5.0.0libs/langgraph-checkpoint-aws/pyproject.toml
PyPIlanggraph>=1.0.0libs/langgraph-checkpoint-aws/pyproject.toml
PyPIboto3>=1.43.64libs/langgraph-checkpoint-aws/pyproject.toml
PyPItyping_extensions>=4.0.0libs/langgraph-checkpoint-aws/pyproject.toml
All dependencies 211

Full resolved dependency set from the GitHub dependency graph: 21 direct and 190 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIbedrock-agentcore1.18.1direct
PyPIbedrock-agentcore1.22.0direct
PyPIboto31.43.55direct
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PyPIlanggraph1.2.9direct
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PyPIlangchain-anthropic1.5.1indirect
PyPIlangchain-anthropic1.7.0indirect
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PyPIlangchain-classic1.0.8indirect
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PyPIlangchain-openai1.6.0indirect
PyPIlangchain-protocol0.0.18indirect
PyPIlangchain-protocol0.0.19indirect
PyPIlangchain-tests1.1.9indirect
PyPIlangchain-text-splitters1.1.2indirect
PyPIlanggraph-checkpoint-aws1.2.3indirect
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PyPItyping-inspection0.4.4indirect
PyPIurllib32.7.0indirect
PyPIuuid-utils0.17.0indirect
PyPIuvicorn0.51.0indirect
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PyPIvalkey6.2.0rc2indirect
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PyPIwcmatch11.0indirect
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PyPIwrapt2.2.2indirect
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PyPIxxhash3.8.1indirect
PyPIxxhash4.0.1indirect
PyPIyarl1.24.5indirect
PyPIzstandard0.25.0indirect
Dependency advisories 0

Installing pypi:langchain-aws@1.7.5 pulls in 40 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.

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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.