公开记录
软件健康报告模式 0.27.0 · 指标 1.13.0 · 2026-07-26 19:04 UTC

antonyrag / ragleap-core

The open-source core of RagLeap — a self-hosted RAG chat engine (document ingestion, retrieval, citations) powering RagLeap's full AI business manager: Voice AI, WhatsApp/Telegram/Discord bots, database & CRM integrations, workflow automation, and a private executive assistant. Foundation layer — hosted platform at ragleap.com

PythonMIT★ 2 星标⑂ 1 复刻始于 2026年7月在 GitHub 上查看 ↗

antonyrag/ragleap-core 的健康指数为 100 分中的 43 分,处于「存在风险」区间。 其得分最高的类别是Engineering Quality(71/100),最低的是Security(27/100)。 最近一次更新在今天。 近期的大部分工作由 1 位贡献者完成。

43
总分 / 100
存在风险

软件健康指数

指标归入加权类别,统一采用 1–100 量表。总体分先取类别加权平均;当公开证据触发高风险司法辖区政策时,评级会按政策调整,并设置 49(有风险)的上限。AI 就绪度不计入总体分。

43
优秀85-100堪称典范;基本满足所有检验标准
良好70-84健康;仅有轻微不足
中等50-69可接受,但存在明显不足;建议进行审查
存在风险30-49存在重大薄弱环节;采用时应保持审慎
危急1-29问题严重(项目被弃置、仅有单一维护者、缺乏基本工程规范)
活力社区与采用可持续性与治理工程质量安全AI 就绪度

评分画像

每条轴代表一个类别。形状比平均值更重要——健康的对象会填满整个图形,而“一峰一谷”式画像意味着某一维度的优势正掩盖另一维度的风险。

所有权

TC Antony个人账户
0 关注者1 个公开仓库始于 2026年3月

该仓库由个人账户拥有。相较于组织支持的项目,单一所有者项目的延续性风险更高。

软件包生态系统

注册表软件包版本月下载量版本数最近发布标签
PyPIragleap-rag0.6.02,085220 天前hybrid-searchllmpgvectorragretrieval-augmented-generationvector-search

按类别列示的指标

活力

项目是否仍有生命——是否仍在编写代码,是否仍在发布版本?

34存在风险 · 占总体的 22%
评分方式
36/36推送新近度 — 最近一次推送于 0 天前
2.8/36提交节奏 — 52 周中有 4 周有提交
17.3/18提交量 — 最近一年 84 次提交
0/10OpenSSF Scorecard:Maintained — project was created within the last 90 days. Please review its contents carefully
所用输入
commits_last_year84
human_commit_share1
days_since_last_push0
active_weeks_last_year4
评分方式
0/27有发布版本 — 未发布任何发布版本
0/36发布时效 — 没有发布版本
0/27发布节奏 — 没有发布版本
0/10OpenSSF Scorecard:Signed-Releases — 无数据
所用输入
releases_count0
已排除计分(无数据或不适用):OpenSSF Scorecard:Signed-Releases。 其余权重已重新归一化。

社区与采用

项目是否拥有用户、下载量与关注度,并具备欢迎贡献者参与的配置?

46存在风险 · 占总体的 18%
评分方式
0/60星标 — 2 个星标
0/25复刻 — 1 个复刻
0/15关注者 — 0 位关注者
所用输入
forks1
stars2
watchers0
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

社区健康

92优秀
评分方式
22.5/22.5README
22.5/22.5许可证 — 可识别的许可证(MIT)
18/18CONTRIBUTING 指南
13.5/13.5行为准则
0/7.2议题模板
6.3/6.3PR 模板
所用输入
has_readme
has_license
has_contributing
has_issue_template
has_code_of_conduct
has_pull_request_template
评分方式
44.3/80月度下载量 — pypi 合计每月 2,085 次下载
0/20注册表被依赖数 — 该生态系统不报告此项
所用输入
packagesragleap-rag
dependents
ecosystemspypi
total_downloads
monthly_downloads2,085
已排除计分(无数据或不适用):注册表被依赖数。 其余权重已重新归一化。

可持续性与治理

项目能否在其成员之外延续——巴士系数、响应能力、由谁支持,以及软件包的维护状况?

36存在风险 · 占总体的 24%
评分方式
9/54巴士系数 — 1 位贡献者贡献了半数提交
0/22.5提交分布 — 头号贡献者编写了 100% 的提交
1.4/13.5贡献者广度 — 1 位贡献者
0/10OpenSSF Scorecard:Contributors — project has 0 contributing companies or organizations -- score normalized to 0
所用输入
bus_factor1
contributors_sampled1
top_contributor_share1
评分方式
0/46.8议题解决 — 0% 的议题已关闭
36.7/38.3PR 接受 — 已裁定的 PR 中 48/50 已合并
0/15OpenSSF Scorecard:Code-Review — Found 0/30 approved changesets -- score normalized to 0
所用输入
merged_prs48
open_issues11
closed_issues0
issue_closed_ratio0
closed_unmerged_prs2
评分方式
10/30所有权背书 — 个人(用户)账户
0/20已验证域名 — 不适用于个人账户
0/25所有者影响力 — antonyrag 有 0 位关注者
3/25既往记录 — 1 个公开仓库,账户约 0 年
所用输入
followers0
owner_typeUser
is_verified
owner_loginantonyrag
public_repos1
account_age_days139
已排除计分(无数据或不适用):已验证域名。 其余权重已重新归一化。
评分方式
25/25已发布且可解析 — pypi 上有 1 个软件包
35/35发布时效 — 最近一次发布于 0 天前
20/20版本历史 — 22 个已发布版本
20/20未被弃用 — 活跃,未被弃用或撤回
所用输入
packagesragleap-rag
ecosystemspypi
any_deprecated
min_days_since_publish0

工程质量

基础的工程与文档实践是否到位?

71良好 · 占总体的 20%

工程实践

68中等
评分方式
24/24CI 工作流 — 1 个工作流
24/24存在测试
0/16Linter 配置
0/9.6Pre-commit 钩子
0/6.4.editorconfig
20/20OpenSSF Scorecard:CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10
所用输入
has_ci
has_tests
has_editorconfig
has_linter_config
has_precommit_config

文档

75良好
评分方式
30/30README
0/25文档目录
15/15文档 / 主页站点 — https://ragleap.com
10/10仓库描述
10/10主题标签 — 18 个主题标签
10/10Wiki
所用输入
topicsai-agents, business-automation, database-integration, document-qa, document-qa-agent, executive-assistant, executive-assistant-agent, intelligent-automation, intelligent-automation-platform, llm, multi-tenant, multi-tenant-saas, open-core, saas, self-hosted, voice-ai, workflow-automation, rag-ai-chatbot
has_wiki
homepagehttps://ragleap.com
has_readme
has_docs_dir
has_description

安全

可见的安全与供应链实践是否稳固,且不存在未解决的高风险司法辖区暴露?

27危急 · 占总体的 16%

安全态势

27危急
评分方式
7.5/7.5Binary-Artifacts — no binaries found in the repo
2.2/7.5Branch-Protection — branch protection is not maximal on development and all release branches
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
0/7.5Code-Review — Found 0/30 approved changesets -- score normalized to 0
0/2.5Contributors — project has 0 contributing companies or organizations -- score normalized to 0
10/10Dangerous-Workflow — no dangerous workflow patterns detected
0/7.5Dependency-Update-Tool — no update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5许可证 — license file detected
0/7.5Maintained — project was created within the last 90 days. Please review its contents carefully
0/5Packaging — 无数据
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 — 无数据
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities — 56 existing vulnerabilities detected
所用输入
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate2.7
已排除计分(无数据或不适用):packaging, signed_releases。 其余权重已重新归一化。

AI 就绪度

该仓库在多大程度上具备与 AI 编码代理协同开发与维护的条件?这是一枚独立的实验性徽章——权重为 0.0,因此单独呈现,不影响总体健康评分。

39存在风险 · 占总体的 0%
评分方式
0/45代理指令 — 没有 CLAUDE.md / AGENTS.md / 编辑器规则
0/15机器可读文档(llms.txt)
40/40可读的提交历史 — 85 次人类提交中有 85 次说明了意图(结构化标题或解释性正文)
所用输入
has_llms_txt
legible_history_share1
agent_instruction_files
agent_instruction_max_bytes
评分方式
0/18一条命令的引导启动
22/22自动化测试
0/11Lint / 格式化配置
0/11静态类型检查
10/10可复现环境 — Dockerfile, lockfile
0/10已体现的代理实践 — 最近 85 次提交中没有代理编写的提交
0/8自动化维护 — 未观察到自动依赖更新
0/10OpenSSF Scorecard:Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
所用输入
has_nix
has_tests
lockfilesuv.lock
has_dockerfile
typed_language
bootstrap_files
has_devcontainer
has_linter_config
typecheck_configs
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0
评分方式
0/45可类型检查的代码 — Python,未配置类型检查
55/55可控的文件大小 — 采样的 70 个源文件中有 0 个超过 60KB
所用输入
primary_languagePython
largest_source_bytes30,306
source_files_sampled70
oversized_source_files0

机器可读接口

40存在风险
评分方式
0/40API 模式(OpenAPI/GraphQL/proto)
0/20MCP 服务器
40/40可运行示例 — examples
所用输入
example_dirsexamples
has_mcp_signal
api_schema_files

关键数据

2GitHub 星标
1贡献者
84最近 12 个月提交数
0距最近推送天数
0发布版本数
1巴士系数(bus factor)
11开放议题
PyPI软件包生态系统数

数据采集警告

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository
  • deps.dev does not index pypi:ragleap-rag@0.6.0; advisories assessed against the repository dependency graph instead

更多细节

OpenSSF Scorecard 2.7 / 10
2.7综合

来自开源项目 OpenSSF Scorecard 的独立、工具无关的安全评估。每项检查奖励的是安全实践本身,而非特定供应商的工具。Scorecard 无法判定的检查项标记为 不适用,并从安全评分中剔除(绝不按零分计)。Scorecard v5.5.0 · 2026-07-26 19:04 UTC

10Binary-Artifactsno binaries found in the repo
3Branch-Protectionbranch protection is not maximal on development and all release branches
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
0Code-ReviewFound 0/30 approved changesets -- score normalized to 0
0Contributorsproject has 0 contributing companies or organizations -- score normalized to 0
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
0Maintainedproject was created within the last 90 days. Please review its contents carefully
不适用Packagingpackaging 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
不适用Signed-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0Vulnerabilities56 existing vulnerabilities detected
直接依赖 4
注册表软件包版本约束清单文件
PyPIpsycopg2-binary>=2.9.0packages/ragleap-rag/pyproject.toml
PyPIrequests>=2.31.0packages/ragleap-rag/pyproject.toml
PyPIpypdf>=4.0.0packages/ragleap-rag/pyproject.toml
PyPIpython-docx>=1.1.0packages/ragleap-rag/pyproject.toml
全部依赖 未采集

本报告未能采集到解析后的依赖集合:GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository

原始 JSON 报告 机器可读
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          "oid": "3a00e4bdd26232a38783aa210683b97e13e475ed",
          "body": "Decouples vector storage from conversation memory - RagLeap now\naccepts vector_backend= to swap storage away from the default\nPgVectorBackend. Conversation memory always uses Postgres regardless\nof vector backend choice, since memory is a separate concern from\nvector storage.\n\nNew: ragleap.vectorsto\n[…]\ns actually run there, not just locally.\n\nFull suite: 83/83 passing (73 existing + 10 new) before this commit.\nVersion bumped 0.5.8 -> 0.6.0 (new public API surface warrants a\nminor bump, not a patch).",
          "is_bot": false,
          "headline": "feat: pluggable vector storage backends (0.6.0) (#62)",
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          "oid": "23f58e3bbbf62a3091e5cf0803ad6eaf73b48347",
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          "is_bot": false,
          "headline": "feat: reranking runs on ONNX Runtime instead of torch/sentence-transf…",
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          "oid": "02be0824dd8682aa297d021bb830a5f205d0fdf5",
          "body": "….7) (#60)\n\nask_stream() and aask_stream() were missing the rerank= and\nmetadata_filter= params that ask()/aask() already had - a real,\npreviously-flagged API inconsistency (Part 5 pending list item).\n\nBoth streaming variants now expand the retrieval pool (top_k*4) and\ncall the reranker when rerank=\n[…]\neranker on both ask_stream() and\naask_stream(), and rerank=False never invoking it. Full suite (71/71)\npassing locally before this commit.\n\nVersion bumped 0.5.6 -> 0.5.7. README and CHANGELOG updated.",
          "is_bot": false,
          "headline": "fix: ask_stream()/aask_stream() missing rerank + metadata_filter (0.5…",
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          "body": "…(#59)\n\nReconstructed from real PR history (#35-#58), not memory - every\nversion entry links to its actual merged PR. Covers the full history:\ninitial release, the embedder_api_key -> EmbeddingConfig breaking\nchange in 0.2.0, every feature through 0.5.6 (Redis cache + batch\ningestion), and the two u\n[…]\nte) that don't warrant their own version bump.\n\nAlso documents the update_document() metadata-loss limitation inline\nat the version it was introduced (0.4.5), matching the locked-in test\nadded in #58.",
          "is_bot": false,
          "headline": "docs: add CHANGELOG.md for ragleap-rag (0.1.0 -> 0.5.6 + unreleased) …",
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          "oid": "58ea145480bf5e6cd60778a992ea99f32b62857f",
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          "is_bot": false,
          "headline": "test: comprehensive pytest suite for ragleap-rag + CI integration (#58)",
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          "oid": "3aa87a65c63bf869bd8d9c22759ee88264df2227",
          "body": "Documents the one constraint that actually matters for background task\nusage: RagLeap's connection pool is per-instance and not fork-safe\nacross processes. Covers the correct pattern (build RagLeap inside\nworker_process_init, not at module import time), a full Redis-broker\ncode example, and an archi\n[…]\n+ collapsed whitespace/alignment) on\nfirst attempt - caught via the standard bracket-view verification step,\nfixed by base64-round-tripping the diagram content rather than pasting\nraw ASCII art again.",
          "is_bot": false,
          "headline": "docs: Celery integration guide + example (#57)",
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          "body": "…#56)\n\nRedis query embedding cache:\n- New RedisQueryEmbeddingCache class (src/ragleap/cache.py), same\n  get/set/clear/stats interface as the existing in-memory cache\n- RagLeap.__init__() gains cache_backend, redis_url, cache_ttl_seconds\n- Verified across process boundaries: two separate RagLeap inst\n[…]\nmethods now have async\ntwins, closing a gap where only 2 of 6 previously did.\n\nVersion bumped 0.5.5 -> 0.5.6 in both pyproject.toml and __init__.py.\nREADME documents both features in this same commit.",
          "is_bot": false,
          "headline": "feat: Redis-backed distributed query cache + ingest_batch() (0.5.6) (…",
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        {
          "oid": "a8c95b69584107bbf0d85fa1b71c2b7e026767e6",
          "body": "Directly answers a question raised this session: should users be\nlocked into just Whisper/Deepgram, or able to bring any provider\nthey judge better (AssemblyAI, Speechmatics, Azure Speech, AWS\nTranscribe, etc.)? Previously the answer was 'wait for ragleap-rag to\nadd it' - now it is not.\n\n- Transcrip\n[…]\n correctly ingested and retrievable via a grounded ask()\nanswer that accurately quoted the custom function's output, and\nvalidation correctly rejected provider='custom' with no transcribe_fn\nsupplied.",
          "is_bot": false,
          "headline": "feat: custom transcription provider support (provider='custom') (#55)",
          "author_name": "TC Antony",
          "author_login": "antonyrag",
          "committed_at": "2026-07-23T18:38:07Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "709237024eb1f34cce15b0d3f2f576a74d619ef7",
          "body": "Fifth and final part of the multi-modal ingestion milestone.\n\n- New video.py: extract_audio_from_video() extracts a video is audio\n  track as MP3 via ffmpeg (a system dependency, not pip-installable,\n  same class as Tesseract for OCR). Proper temp file cleanup on all\n  paths including error cases.\n-\n[…]\n video content, not just placeholder\nbytes. Combined with the live Deepgram transcription test above, both\nhalves of ingest_video()'s pipeline are now genuinely proven, not\njust structurally verified.",
          "is_bot": false,
          "headline": "feat: video ingestion (ffmpeg audio extraction + transcription) (#54)",
          "author_name": "TC Antony",
          "author_login": "antonyrag",
          "committed_at": "2026-07-23T09:06:35Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "1b2e7c697824a3e9411052ca6b9f029c452c4595",
          "body": "Fourth part of the multi-modal ingestion milestone. Pluggable\ntranscription providers rather than a hardcoded Whisper-only path,\ndirectly addressing a real question raised this session: does\nWhisper handle multi-language/low-volume/noisy audio correctly, or\nshould users be able to bring their own pr\n[…]\nnd\ntranscription against a real provider is untested and should be done\nin a follow-up once a key is available, before this can be considered\nfully proven the way every other feature this session was.",
          "is_bot": false,
          "headline": "feat: audio ingestion (Whisper + Deepgram, pluggable) (#53)",
          "author_name": "TC Antony",
          "author_login": "antonyrag",
          "committed_at": "2026-07-22T18:59:51Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "e08158c35e4908010b796119cb4d8eedefeab180",
          "body": "Third part of the multi-modal ingestion milestone. Two genuinely\ndifferent techniques for two different kinds of images - one does\nnot substitute for the other.\n\n- New ocr.py: extract_text_from_image() wraps pytesseract, reads\n  literal visible text (scanned documents, screenshots, photos of\n  text)\n[…]\nle); vision\ncaptioning correctly identified 'red' and 'circle' from an image\ncontaining a colored shape and zero text, proving it's genuinely\ndescribing visual content rather than falling back to OCR.",
          "is_bot": false,
          "headline": "feat: image ingestion (OCR + vision captioning) (#52)",
          "author_name": "TC Antony",
          "author_login": "antonyrag",
          "committed_at": "2026-07-22T05:14:18Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "958238e564296073d04afbb95d03f3b3558a1a09",
          "body": "Missed in the previous commit - only pyproject.toml's version was\nstaged, __init__.py's __version__ was left at 0.5.0. Caught via a\nroutine git status check before publishing, not after.",
          "is_bot": false,
          "headline": "fix: bump __version__ to match pyproject.toml (0.5.1) (#51)",
          "author_name": "TC Antony",
          "author_login": "antonyrag",
          "committed_at": "2026-07-22T04:40:47Z",
          "body_truncated": false,
          "is_coding_agent": false
        },
        {
          "oid": "bcd10be7d2269508e717716ad759735fe19af886",
          "body": "Second part of the multi-modal ingestion milestone. Previously\ningest()/ingest_text() supported only txt/pdf/docx - a real gap\nagainst LangChain's 100+ document loaders. This adds 25 more format\nhandlers across office documents, spreadsheets, structured data,\nmarkup, archives, and subtitle files.\n\n-\n[…]\nxtraction via a real openpyxl workbook), ZIP (correctly\nrecursed into and extracted both a nested .txt and .json file), and\nSRT (cue numbers and timestamps correctly stripped, spoken lines\npreserved).",
          "is_bot": false,
          "headline": "feat: expanded document format support (28 formats) (#50)",
          "author_name": "TC Antony",
          "author_login": "antonyrag",
          "committed_at": "2026-07-22T04:31:22Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "3f1f732fe8555666be42960bd0d8bc0e263f2c1b",
          "body": "First of the multi-modal ingestion additions - directly closes part\nof the 'document loader breadth' gap flagged against LangChain, which\nhas 100+ loaders vs ragleap-rag's previous txt/pdf/docx-only support.\n\n- New web.py: fetch_url_text() wraps trafilatura, extracting clean\n  readable text (strippi\n[…]\non (5\nchunks), then asked 'What is retrieval-augmented generation?' and got\na genuinely accurate, well-grounded answer with correct citations\nshowing the URL as document_name across 3 distinct chunks.",
          "is_bot": false,
          "headline": "feat: URL ingestion (ingest_url) (#49)",
          "author_name": "TC Antony",
          "author_login": "antonyrag",
          "committed_at": "2026-07-21T19:08:42Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "457056ac1b16ca73af2e43c1a2987f25d3f306a1",
          "body": "Resolves a real ambiguity flagged in the gap analysis: a citation\nlike \"(Source 1)\" in an answer previously gave no way to tell\nwhether it referred to a whole document or one specific passage\nwithin it. It was always chunk-level internally, but this was never\ndocumented or exposed - a real gap for a\n[…]\ncit chunk-level format, and the returned citations\nlist correctly mapped each source_number to the right document_name,\nchunk_index, and a verifiable text_preview matching what was actually\nretrieved.",
          "is_bot": false,
          "headline": "feat: citation clarity (chunk-level, structured citations) (#48)",
          "author_name": "TC Antony",
          "author_login": "antonyrag",
          "committed_at": "2026-07-21T18:48:27Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "fc0099285c13d48e7803b873f8d69e9a5ff097c6",
          "body": "Adds defensive measures at ingest time, a real gap flagged directly\nagainst RAG's known attack surface - malicious content embedded and\nlater surfaced to an LLM via retrieval.\n\nHonest scope, stated explicitly in the module docstring and README:\nthis reduces risk, it does not eliminate it. Prompt inj\n[…]\nary business text (no\nfalse positive); confirmed ingest_text() logs the expected WARNING for\nsuspicious content but still successfully ingests it, proving this is\na signal, not a block, as documented.",
          "is_bot": false,
          "headline": "feat: content sanitization and injection-risk detection (#47)",
          "author_name": "TC Antony",
          "author_login": "antonyrag",
          "committed_at": "2026-07-21T09:50:05Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "813ac387af213f39273cfb1d4c07fd23dd907cc3",
          "body": "…gs) (#46)\n\nAdds JSONB metadata storage and Postgres-native containment filtering,\nthe basis for multi-tenant isolation - a real gap flagged directly\nagainst the resume's claimed workspace-scoped multi-tenant work,\nwhich had no equivalent in the public API until now.\n\n- New metadata JSONB column on \n[…]\nenant: acme} answer\nmentioned ONLY the acme secret, never the globex one, and vice versa -\nconcrete proof the JSONB filter genuinely restricts retrieval rather\nthan being silently accepted as a no-op.",
          "is_bot": false,
          "headline": "feat: metadata filtering (multi-tenant, date-range, arbitrary JSON ta…",
          "author_name": "TC Antony",
          "author_login": "antonyrag",
          "committed_at": "2026-07-21T09:40:28Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "2b10adc9acdced8c74060fe309a868a6ad104bdd",
          "body": "…ument) (#45)\n\nAdds methods to manage previously ingested content, which was\npreviously missing entirely - a real production gap since content\ninevitably needs removing or refreshing over time.\n\n- list_documents(limit, offset): documents newest-first, joined with\n  a live chunk count via GROUP BY, n\n[…]\nts,\nconfirmed ask() reflects the updated content (not the original) after\nupdate, confirmed delete_document removes a real document and\ncorrectly returns False (not an exception) for a nonexistent id.",
          "is_bot": false,
          "headline": "feat: document lifecycle (list_documents, delete_document, update_doc…",
          "author_name": "TC Antony",
          "author_login": "antonyrag",
          "committed_at": "2026-07-21T08:44:46Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "955f1c6e15fca33510901499e144b82445910c31",
          "body": "Adds async equivalents for every method that touches the database or\nan API, for use inside async web servers (FastAPI, etc.) where a\nblocking sync call would stall the event loop.\n\nHonest implementation note: these wrap the existing, tested sync\nmethods via asyncio.to_thread() rather than a from-sc\n[…]\nency proof: 3 concurrent aask() calls\ncompleted in 5.94s total, well under 3x a single call's typical time,\nconfirming the threading wrapper is genuinely non-blocking rather than\nsilently serializing.",
          "is_bot": false,
          "headline": "feat: async support (aingest, aingest_text, aask, aask_stream) (#44)",
          "author_name": "TC Antony",
          "author_login": "antonyrag",
          "committed_at": "2026-07-21T08:28:15Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "60578a0cb46f69d151d6270094d9dddb2d90b7ce",
          "body": "Repeated identical queries were re-embedding from scratch every time.\nAdds an in-memory LRU cache (1000 entries by default) keyed on\n(query text, embedding model) - safe to enable by default since an\nembedding is a pure function of its inputs.\n\n- New QueryEmbeddingCache (cache.py): simple OrderedDic\n[…]\nes + Gemini - three calls (repeat query, repeat same query,\nthen a different query) produced exactly the expected hits=1, misses=2,\nwith the cache-hit call measurably faster than the cache-miss calls.",
          "is_bot": false,
          "headline": "feat: query embedding caching (in-memory LRU, opt-out) (#43)",
          "author_name": "TC Antony",
          "author_login": "antonyrag",
          "committed_at": "2026-07-21T05:12:09Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "5079e63e90d4f3e0ad7e2a1340094620877b5faa",
          "body": "Every DB-touching method (ingest_text, ask via retrieval, memory's\nadd_message/get_history/clear_session) previously opened a brand-new\npsycopg2 connection per call and closed it immediately after - a\nfresh TCP handshake + Postgres auth on every single operation, real\navoidable latency especially un\n[…]\nssful ingest,\n5 sequential ask() calls with session memory completing without\nconnection errors, history correctly accumulating and clearing.\nNo functional regressions in retrieval or memory behavior.",
          "is_bot": false,
          "headline": "feat: connection pooling for all database access (#41)",
          "author_name": "TC Antony",
          "author_login": "antonyrag",
          "committed_at": "2026-07-21T04:50:05Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "02d36d63d73b2e1f99ba0323f0613b19d243a785",
          "body": "PR #39 shipped cross-encoder reranking but the README was not\nupdated - same gap the conversation memory feature had before\n(PR #38 fixed that one). Adding this now rather than letting it\ngo unnoticed for another release cycle.\n\nNew Reranking section covers: rerank=True usage, the [rerank]\nextra ins\n[…]\nith full python3 -m build, confirmed via wheel\nMETADATA inspection that the Reranking section and rerank=True\nusage are present, published as part of 0.4.0:\nhttps://pypi.org/project/ragleap-rag/0.4.0/",
          "is_bot": false,
          "headline": "docs: document reranking (rerank=True) (#40)",
          "author_name": "TC Antony",
          "author_login": "antonyrag",
          "committed_at": "2026-07-21T04:29:33Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "854390e4fa4ec5d09f676a1ea416b59f47d7626b",
          "body": "Adds rerank=True option to ask() for cross-encoder reranking of\nretrieved chunks before generation. Off by default — no breaking\nchange, no new dependency unless explicitly opted into.\n\n- New RerankerService (reranking.py), lazy-loads sentence-transformers'\n  CrossEncoder (cross-encoder/ms-marco-Min\n[…]\ny (only on\nfirst rerank=True call, visible via the weights-loading progress bar),\nand reranked results genuinely differ from unranked top-k (better\nsource precision in the reranked answer's citation).",
          "is_bot": false,
          "headline": "feat: cross-encoder reranking (session-scoped, opt-in) (#39)",
          "author_name": "TC Antony",
          "author_login": "antonyrag",
          "committed_at": "2026-07-21T03:55:17Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "774e099909c54b183d86a82f695ee4fe634b2883",
          "body": "…ory (#38)\n\nThe Reliability/fallback example in README.md still referenced the\npre-0.2.0 embedder_api_key= parameter, which no longer exists on\nRagLeap.__init__() (replaced by embedder=EmbeddingConfig(...) in PR\n#36). It was still showing on PyPI as the documented usage for that\nexample even after 0\n[…]\n was accidentally wheel-only), confirmed via wheel METADATA\ninspection that embedder_api_key is gone and the new memory docs are\npresent, published to PyPI: https://pypi.org/project/ragleap-rag/0.3.1/",
          "is_bot": false,
          "headline": "docs: fix stale embedder_api_key reference, document conversation mem…",
          "author_name": "TC Antony",
          "author_login": "antonyrag",
          "committed_at": "2026-07-20T19:15:40Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "ae9477ac39851c1c14453fa12aaa011542a5ced8",
          "body": "…) (#37)\n\nAdds multi-turn conversation memory to ask()/ask_stream() via an\nopt-in session_id parameter. Omitting session_id preserves fully\nstateless behavior — no breaking change.\n\n- New ConversationMemory class (memory.py): add_message, get_history,\n  clear_session, build_history_prompt — mirrors \n[…]\ntly\nresolved pronoun references ('he', 'his') using only stored context,\nhistory correctly persisted and retrievable via get_history(), and\nclear_session() confirmed to fully wipe a session's history.",
          "is_bot": false,
          "headline": "feat: persistent conversation memory (session-scoped, Postgres-backed…",
          "author_name": "TC Antony",
          "author_login": "antonyrag",
          "committed_at": "2026-07-20T18:55:43Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "84f6725f6059be59aaf313b4d396677a9e0e5180",
          "body": "Breaking change: RagLeap.__init__() now takes embedder: EmbeddingConfig\ninstead of embedder_api_key: Optional[str]. Fixes a design flaw where\nembeddings were hardcoded to Gemini regardless of the [gemini]/[anthropic]\n/[openai] extras, contradicting the package's BYOK claim — those extras\nonly ever g\n[…]\ned to 0.2.0, published to PyPI: https://pypi.org/project/ragleap-rag/0.2.0/\n- Verified end-to-end: fresh venv install, real ingest + ask against\n  live Postgres + Gemini, correct token usage reporting",
          "is_bot": false,
          "headline": "feat: pluggable embeddings via EmbeddingConfig (gemini + openai) (#36)",
          "author_name": "TC Antony",
          "author_login": "antonyrag",
          "committed_at": "2026-07-20T18:36:31Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "a5a9a4be93193b14e1760fd9d51e56da357debd3",
          "body": "…(#35)\n\nFirst installable package split out from ragleap-core, per the\nPhase A/B/C ecosystem plan: pip install ragleap-rag, own pyproject.toml,\nown PyPI listing (name confirmed available).\n\nDeliberately RAG-only — no knowledge-graph, language-detection, or\nintegrations coupling baked in. Those becom\n[…]\ngainst the live\nPostgres database, getting a correct answer with real token usage\nnumbers back. This proves the package works standalone, not just\nthat the files happen to compile inside the monorepo.",
          "is_bot": false,
          "headline": "feat: ragleap-rag — standalone pip-installable RAG package (Phase A) …",
          "author_name": "TC Antony",
          "author_login": "antonyrag",
          "committed_at": "2026-07-18T17:44:50Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "e3804cbc508704cd0aa7080002afeac6e41f098f",
          "body": "…iability docs (#34)\n\n- Restore the 'Integrations' README section and Features table row,\n  which were lost during a prior merge (PR #22's docs commit never\n  made it into that squash merge — confirmed via git log --follow\n  showing the docs commit missing from the merged diff). Also fixes\n  the hos\n[…]\nncluding known limitations\n  (no streaming usage reporting yet, character-count approximation\n  for context budget, hybrid search not yet benchmarked for ranking\n  quality on a multi-document corpus).",
          "is_bot": false,
          "headline": "docs: restore lost Integrations section, add Retrieval/Generation/Rel…",
          "author_name": "TC Antony",
          "author_login": "antonyrag",
          "committed_at": "2026-07-18T11:20:53Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "6596f771faeb508a7a48a7bb2185e00a319f6e0b",
          "body": "Real, verifiable token optimization — not a marketing claim, numbers\na developer can reproduce themselves.\n\n- core/generation.py: generate_answer() now returns actual token usage\n  (prompt_tokens, completion_tokens, total_tokens) pulled from each\n  provider's real response (Gemini's usage_metadata, \n[…]\ned prompt+completion\nbecause thinking-model 'thoughts' tokens are billed but not part of\nthe visible split — our reporting surfaces the real number rather\nthan a recalculated one that would hide this.",
          "is_bot": false,
          "headline": "feat: real token usage reporting + context budget trimming (#33)",
          "author_name": "TC Antony",
          "author_login": "antonyrag",
          "committed_at": "2026-07-18T05:20:51Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "79c351b18297ca58227a2660e5cf80a4b49df2db",
          "body": "If the primary LLM_PROVIDER fails (rate limit, outage, bad key), retry\nwith each provider in LLM_FALLBACK_PROVIDERS (comma-separated), in\norder, before giving up.\n\n- core/generation.py: refactored provider resolution into a standalone\n  _resolve_provider_config() function (required=True for the prim\n[…]\nh generate_answer() and generate_answer_stream().\nConfirmed provider_used flows correctly through the full HTTP /chat\nendpoint under normal (non-fallback) operation, returning\nprovider_used: 'gemini'.",
          "is_bot": false,
          "headline": "feat: LLM provider fallback chain (#31)",
          "author_name": "TC Antony",
          "author_login": "antonyrag",
          "committed_at": "2026-07-17T19:06:21Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "a2a6c1a9589c99e4134fa697868704383016a147",
          "body": "…s (#30)\n\nReal, tested developer-facing controls, not surface-level flags:\n\n- core/retrieval.py: new search_sparse_chunks() (Postgres full-text\n  search via websearch_to_tsquery + ts_rank) and search_hybrid_chunks()\n  (combines dense + sparse via Reciprocal Rank Fusion, RRF_K=60,\n  still applies the\n[…]\nefit on a multi-document corpus with genuinely conflicting dense\nvs. sparse rankings — only single-document correctness. Worth a\nfollow-up benchmark before making comparative retrieval-quality claims.",
          "is_bot": false,
          "headline": "feat: hybrid search (dense+sparse), streaming, and generation control…",
          "author_name": "TC Antony",
          "author_login": "antonyrag",
          "committed_at": "2026-07-17T18:39:37Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "200493c14154dd483fa9b047eea1bb7915bfda7c",
          "body": "… (#23)\n\n- Add a note distinguishing this repo (MIT, free, no license key) from\n  install.ragleap.com (separate paid, license-gated self-hosted product)\n- Update the status badge, stale since it only listed 3 channels —\n  now reflects 4 channels + Knowledge Graph + multilingual detection\n  + integrations, all merged",
          "is_bot": false,
          "headline": "docs: clarify install.ragleap.com naming overlap, update status badge…",
          "author_name": "TC Antony",
          "author_login": "antonyrag",
          "committed_at": "2026-07-17T04:31:03Z",
          "body_truncated": false,
          "is_coding_agent": false
        },
        {
          "oid": "59b9fa5557ebff3fff6fcfb868307419e468075a",
          "body": "Opens the integrations/CRM connectors feature, ported from production's\napi/addon_models.py + api/addon_services.py (workspace scoping removed,\nsingle-tenant; Django ORM replaced with plain dataclass + psycopg2,\nmatching core/ingest.py's pattern).\n\n- core/integrations/base.py: DataSource dataclass, \n[…]\nmatically\ninjected into chat responses — core/chat.py would need a lookup by\nuser_identifier per channel, which requires each channel adapter to\nknow its own user's identifier, a reasonable next step.",
          "is_bot": false,
          "headline": "feat: add external data source integrations (9 connectors) (#22)",
          "author_name": "TC Antony",
          "author_login": "antonyrag",
          "committed_at": "2026-07-17T04:15:17Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "e1226546298c2278595c1a2451813fe4d530aa6b",
          "body": "* feat: add language detection (langdetect) to ingestion and chat\n\n- Add core/language.py: LanguageDetector class ported from production's\n  multilingual/language_detector.py, single-tenant, Django settings\n  replaced with .env vars. Includes script-based heuristics (CJK/Hangul/\n  Kana), confidence \n[…]\n confirmed working, and known limitations (langdetect's language\n  coverage vs. the hosted platform's, short-query misdetection risk,\n  and that detection doesn't yet steer the AI's response language)",
          "is_bot": false,
          "headline": "feat: Language detection (langdetect) for ingestion and chat (#21)",
          "author_name": "TC Antony",
          "author_login": "antonyrag",
          "committed_at": "2026-07-16T09:49:30Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
        {
          "oid": "ffe336437d24a5f4dc70d2b3ad774b50a9fd44ce",
          "body": "- Add core/language.py: LanguageDetector class ported from production's\n  multilingual/language_detector.py, single-tenant, Django settings\n  replaced with .env vars. Includes script-based heuristics (CJK/Hangul/\n  Kana), confidence thresholds, and query-specific overrides (ASCII\n  ratio, context sn\n[…]\nery was detected as Italian) — this is an inherent langdetect\nlimitation on short text, not a regression from the port; production's\nown heuristics exist specifically to mitigate (not eliminate) this.",
          "is_bot": false,
          "headline": "feat: add language detection (langdetect) to ingestion and chat (#20)",
          "author_name": "TC Antony",
          "author_login": "antonyrag",
          "committed_at": "2026-07-16T09:39:54Z",
          "body_truncated": true,
          "is_coding_agent": false
        },
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                "detail": null,
                "points": 18,
                "status": "met",
                "details": [],
                "max_points": 18
              },
              {
                "key": "code_of_conduct",
                "name": "Code of conduct",
                "detail": null,
                "points": 13.5,
                "status": "met",
                "details": [],
                "max_points": 13.5
              },
              {
                "key": "issue_template",
                "name": "Issue template",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 7.2
              },
              {
                "key": "pr_template",
                "name": "PR template",
                "detail": null,
                "points": 6.3,
                "status": "met",
                "details": [],
                "max_points": 6.3
              }
            ]
          },
          {
            "key": "ecosystem_adoption",
            "band": "moderate",
            "name": "Ecosystem adoption (downloads)",
            "note": "Excluded from scoring (no data or not applicable): Registry dependents. Remaining weights renormalized.",
            "notes": [
              {
                "code": "excluded_no_data",
                "params": {
                  "components": [
                    "registry_dependents"
                  ]
                }
              },
              {
                "code": "weights_renormalized",
                "params": {}
              }
            ],
            "value": 55,
            "inputs": {
              "packages": [
                "ragleap-rag"
              ],
              "dependents": null,
              "ecosystems": "pypi",
              "total_downloads": null,
              "monthly_downloads": 2085
            },
            "components": [
              {
                "key": "monthly_downloads",
                "name": "Monthly downloads",
                "detail": "2,085 downloads/month across pypi",
                "points": 44.3,
                "status": "partial",
                "details": [
                  {
                    "code": "downloads_monthly",
                    "params": {
                      "count": 2085,
                      "ecosystems": "pypi"
                    }
                  }
                ],
                "max_points": 80
              },
              {
                "key": "registry_dependents",
                "name": "Registry dependents",
                "detail": "not reported by this ecosystem",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "not_reported_by_this_ecosystem",
                    "params": {}
                  }
                ],
                "max_points": 20
              }
            ]
          }
        ],
        "description": "Does the project have users, downloads, attention, and a welcoming setup for contributors?"
      },
      {
        "key": "governance",
        "band": "at_risk",
        "name": "Sustainability & Governance",
        "value": 36,
        "weight": 0.24,
        "metrics": [
          {
            "key": "maintainer_resilience",
            "band": "critical",
            "name": "Maintainer resilience (bus factor)",
            "note": null,
            "notes": [],
            "value": 10,
            "inputs": {
              "bus_factor": 1,
              "contributors_sampled": 1,
              "top_contributor_share": 1
            },
            "components": [
              {
                "key": "bus_factor",
                "name": "Bus factor",
                "detail": "1 contributor(s) cover half of all commits",
                "points": 9,
                "status": "partial",
                "details": [
                  {
                    "code": "bus_factor",
                    "params": {
                      "count": 1
                    }
                  }
                ],
                "max_points": 54
              },
              {
                "key": "commit_distribution",
                "name": "Commit distribution",
                "detail": "top contributor authored 100% of commits",
                "points": 0,
                "status": "missed",
                "details": [
                  {
                    "code": "top_contributor_share",
                    "params": {
                      "share": 100
                    }
                  }
                ],
                "max_points": 22.5
              },
              {
                "key": "contributor_breadth",
                "name": "Contributor breadth",
                "detail": "1 contributors",
                "points": 1.4,
                "status": "partial",
                "details": [
                  {
                    "code": "contributors_sampled",
                    "params": {
                      "count": 1
                    }
                  }
                ],
                "max_points": 13.5
              },
              {
                "key": "openssf_scorecard_contributors",
                "name": "OpenSSF Scorecard: Contributors",
                "detail": "project has 0 contributing companies or organizations -- score normalized to 0",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 10
              }
            ]
          },
          {
            "key": "responsiveness",
            "band": "at_risk",
            "name": "Issue & PR responsiveness",
            "note": null,
            "notes": [],
            "value": 37,
            "inputs": {
              "merged_prs": 48,
              "open_issues": 11,
              "closed_issues": 0,
              "issue_closed_ratio": 0,
              "closed_unmerged_prs": 2
            },
            "components": [
              {
                "key": "issue_resolution",
                "name": "Issue resolution",
                "detail": "0% of issues closed",
                "points": 0,
                "status": "missed",
                "details": [
                  {
                    "code": "issues_closed_share",
                    "params": {
                      "share": 0
                    }
                  }
                ],
                "max_points": 46.75
              },
              {
                "key": "pr_acceptance",
                "name": "PR acceptance",
                "detail": "48/50 decided PRs merged",
                "points": 36.7,
                "status": "partial",
                "details": [
                  {
                    "code": "decided_prs_merged",
                    "params": {
                      "merged": 48,
                      "decided": 50
                    }
                  }
                ],
                "max_points": 38.25
              },
              {
                "key": "openssf_scorecard_code_review",
                "name": "OpenSSF Scorecard: Code-Review",
                "detail": "Found 0/30 approved changesets -- score normalized to 0",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 15
              }
            ]
          },
          {
            "key": "stewardship",
            "band": "critical",
            "name": "Ownership & stewardship",
            "note": "Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.",
            "notes": [
              {
                "code": "excluded_no_data",
                "params": {
                  "components": [
                    "verified_domain"
                  ]
                }
              },
              {
                "code": "weights_renormalized",
                "params": {}
              }
            ],
            "value": 16,
            "inputs": {
              "followers": 0,
              "owner_type": "User",
              "is_verified": null,
              "owner_login": "antonyrag",
              "public_repos": 1,
              "account_age_days": 139
            },
            "components": [
              {
                "key": "ownership_backing",
                "name": "Ownership backing",
                "detail": "personal (user) account",
                "points": 10,
                "status": "partial",
                "details": [
                  {
                    "code": "owner_personal",
                    "params": {}
                  }
                ],
                "max_points": 30
              },
              {
                "key": "verified_domain",
                "name": "Verified domain",
                "detail": "not applicable to user accounts",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "not_applicable_to_user_accounts",
                    "params": {}
                  }
                ],
                "max_points": 20
              },
              {
                "key": "owner_reach",
                "name": "Owner reach",
                "detail": "0 followers of antonyrag",
                "points": 0,
                "status": "missed",
                "details": [
                  {
                    "code": "owner_followers",
                    "params": {
                      "count": 0,
                      "login": "antonyrag"
                    }
                  }
                ],
                "max_points": 25
              },
              {
                "key": "track_record",
                "name": "Track record",
                "detail": "1 public repos, account ~0 yr old",
                "points": 3,
                "status": "partial",
                "details": [
                  {
                    "code": "public_repos",
                    "params": {
                      "count": 1
                    }
                  },
                  {
                    "code": "account_age_years",
                    "params": {
                      "years": 0
                    }
                  }
                ],
                "max_points": 25
              }
            ]
          },
          {
            "key": "package_maintenance",
            "band": "excellent",
            "name": "Package maintenance",
            "note": null,
            "notes": [],
            "value": 100,
            "inputs": {
              "packages": [
                "ragleap-rag"
              ],
              "ecosystems": "pypi",
              "any_deprecated": false,
              "min_days_since_publish": 0
            },
            "components": [
              {
                "key": "published_resolvable",
                "name": "Published & resolvable",
                "detail": "1 package(s) on pypi",
                "points": 25,
                "status": "met",
                "details": [
                  {
                    "code": "packages_published",
                    "params": {
                      "count": 1,
                      "ecosystems": "pypi"
                    }
                  }
                ],
                "max_points": 25
              },
              {
                "key": "publish_recency",
                "name": "Publish recency",
                "detail": "latest publish 0 days ago",
                "points": 35,
                "status": "met",
                "details": [
                  {
                    "code": "publish_recency",
                    "params": {
                      "days": 0
                    }
                  }
                ],
                "max_points": 35
              },
              {
                "key": "version_history",
                "name": "Version history",
                "detail": "22 published versions",
                "points": 20,
                "status": "met",
                "details": [
                  {
                    "code": "published_versions",
                    "params": {
                      "count": 22
                    }
                  }
                ],
                "max_points": 20
              },
              {
                "key": "not_deprecated",
                "name": "Not deprecated",
                "detail": "active, not deprecated or yanked",
                "points": 20,
                "status": "met",
                "details": [
                  {
                    "code": "package_not_deprecated",
                    "params": {}
                  }
                ],
                "max_points": 20
              }
            ]
          }
        ],
        "description": "Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?"
      },
      {
        "key": "engineering",
        "band": "good",
        "name": "Engineering Quality",
        "value": 71,
        "weight": 0.2,
        "metrics": [
          {
            "key": "engineering_practices",
            "band": "moderate",
            "name": "Engineering practices",
            "note": null,
            "notes": [],
            "value": 68,
            "inputs": {
              "has_ci": true,
              "has_tests": true,
              "has_editorconfig": false,
              "has_linter_config": false,
              "has_precommit_config": false
            },
            "components": [
              {
                "key": "ci_workflows",
                "name": "CI workflows",
                "detail": "1 workflow(s)",
                "points": 24,
                "status": "met",
                "details": [
                  {
                    "code": "ci_workflows",
                    "params": {
                      "count": 1
                    }
                  }
                ],
                "max_points": 24
              },
              {
                "key": "tests_present",
                "name": "Tests present",
                "detail": null,
                "points": 24,
                "status": "met",
                "details": [],
                "max_points": 24
              },
              {
                "key": "linter_config",
                "name": "Linter config",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 16
              },
              {
                "key": "pre_commit_hooks",
                "name": "Pre-commit hooks",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 9.6
              },
              {
                "key": "editorconfig",
                "name": ".editorconfig",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 6.4
              },
              {
                "key": "openssf_scorecard_ci_tests",
                "name": "OpenSSF Scorecard: CI-Tests",
                "detail": "30 out of 30 merged PRs checked by a CI test -- score normalized to 10",
                "points": 20,
                "status": "met",
                "details": [],
                "max_points": 20
              }
            ]
          },
          {
            "key": "documentation",
            "band": "good",
            "name": "Documentation",
            "note": null,
            "notes": [],
            "value": 75,
            "inputs": {
              "topics": [
                "ai-agents",
                "business-automation",
                "database-integration",
                "document-qa",
                "document-qa-agent",
                "executive-assistant",
                "executive-assistant-agent",
                "intelligent-automation",
                "intelligent-automation-platform",
                "llm",
                "multi-tenant",
                "multi-tenant-saas",
                "open-core",
                "saas",
                "self-hosted",
                "voice-ai",
                "workflow-automation",
                "rag-ai-chatbot"
              ],
              "has_wiki": true,
              "homepage": "https://ragleap.com",
              "has_readme": true,
              "has_docs_dir": false,
              "has_description": true
            },
            "components": [
              {
                "key": "readme",
                "name": "README",
                "detail": null,
                "points": 30,
                "status": "met",
                "details": [],
                "max_points": 30
              },
              {
                "key": "documentation_directory",
                "name": "Documentation directory",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 25
              },
              {
                "key": "documentation_homepage_site",
                "name": "Documentation / homepage site",
                "detail": "https://ragleap.com",
                "points": 15,
                "status": "met",
                "details": [],
                "max_points": 15
              },
              {
                "key": "repository_description",
                "name": "Repository description",
                "detail": null,
                "points": 10,
                "status": "met",
                "details": [],
                "max_points": 10
              },
              {
                "key": "topics",
                "name": "Topics",
                "detail": "18 topics",
                "points": 10,
                "status": "met",
                "details": [
                  {
                    "code": "topics_count",
                    "params": {
                      "count": 18
                    }
                  }
                ],
                "max_points": 10
              },
              {
                "key": "wiki",
                "name": "Wiki",
                "detail": null,
                "points": 10,
                "status": "met",
                "details": [],
                "max_points": 10
              }
            ]
          }
        ],
        "description": "Are baseline engineering and documentation practices in place?"
      },
      {
        "key": "security",
        "band": "critical",
        "name": "Security",
        "value": 27,
        "weight": 0.16,
        "metrics": [
          {
            "key": "security_posture",
            "band": "critical",
            "name": "Security posture",
            "note": "Excluded from scoring (no data or not applicable): Packaging, Signed-Releases. Remaining weights renormalized.",
            "notes": [
              {
                "code": "excluded_no_data",
                "params": {
                  "components": [
                    "packaging",
                    "signed_releases"
                  ]
                }
              },
              {
                "code": "weights_renormalized",
                "params": {}
              }
            ],
            "value": 27,
            "inputs": {
              "source": "openssf_scorecard",
              "checks_evaluated": 16,
              "scorecard_version": "v5.5.0",
              "checks_inconclusive": 2,
              "scorecard_aggregate": 2.7
            },
            "components": [
              {
                "key": "binary_artifacts",
                "name": "Binary-Artifacts",
                "detail": "no binaries found in the repo",
                "points": 7.5,
                "status": "met",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "branch_protection",
                "name": "Branch-Protection",
                "detail": "branch protection is not maximal on development and all release branches",
                "points": 2.2,
                "status": "partial",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "ci_tests",
                "name": "CI-Tests",
                "detail": "30 out of 30 merged PRs checked by a CI test -- score normalized to 10",
                "points": 2.5,
                "status": "met",
                "details": [],
                "max_points": 2.5
              },
              {
                "key": "cii_best_practices",
                "name": "CII-Best-Practices",
                "detail": "no effort to earn an OpenSSF best practices badge detected",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 2.5
              },
              {
                "key": "code_review",
                "name": "Code-Review",
                "detail": "Found 0/30 approved changesets -- score normalized to 0",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "contributors",
                "name": "Contributors",
                "detail": "project has 0 contributing companies or organizations -- score normalized to 0",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 2.5
              },
              {
                "key": "dangerous_workflow",
                "name": "Dangerous-Workflow",
                "detail": "no dangerous workflow patterns detected",
                "points": 10,
                "status": "met",
                "details": [],
                "max_points": 10
              },
              {
                "key": "dependency_update_tool",
                "name": "Dependency-Update-Tool",
                "detail": "no update tool detected",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "fuzzing",
                "name": "Fuzzing",
                "detail": "project is not fuzzed",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 5
              },
              {
                "key": "license",
                "name": "License",
                "detail": "license file detected",
                "points": 2.5,
                "status": "met",
                "details": [],
                "max_points": 2.5
              },
              {
                "key": "maintained",
                "name": "Maintained",
                "detail": "project was created within the last 90 days. Please review its contents carefully",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "packaging",
                "name": "Packaging",
                "detail": "packaging workflow not detected",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "no_data",
                    "params": {}
                  }
                ],
                "max_points": 5
              },
              {
                "key": "pinned_dependencies",
                "name": "Pinned-Dependencies",
                "detail": "dependency not pinned by hash detected -- score normalized to 0",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 5
              },
              {
                "key": "sast",
                "name": "SAST",
                "detail": "SAST tool is not run on all commits -- score normalized to 0",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 5
              },
              {
                "key": "security_policy",
                "name": "Security-Policy",
                "detail": "security policy file not detected",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 5
              },
              {
                "key": "signed_releases",
                "name": "Signed-Releases",
                "detail": "no releases found",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "no_data",
                    "params": {}
                  }
                ],
                "max_points": 7.5
              },
              {
                "key": "token_permissions",
                "name": "Token-Permissions",
                "detail": "detected GitHub workflow tokens with excessive permissions",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "vulnerabilities",
                "name": "Vulnerabilities",
                "detail": "56 existing vulnerabilities detected",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 7.5
              }
            ]
          }
        ],
        "description": "Are visible security and supply-chain practices strong, with no malicious dependency and no unresolved high-risk jurisdiction exposure?"
      },
      {
        "key": "ai_readiness",
        "band": "at_risk",
        "name": "AI Readiness",
        "value": 39,
        "weight": 0,
        "metrics": [
          {
            "key": "ai_agent_context",
            "band": "at_risk",
            "name": "Agent context & guidance",
            "note": null,
            "notes": [],
            "value": 40,
            "inputs": {
              "has_llms_txt": false,
              "legible_history_share": 1,
              "agent_instruction_files": [],
              "agent_instruction_max_bytes": null
            },
            "components": [
              {
                "key": "agent_instructions",
                "name": "Agent instructions",
                "detail": "no CLAUDE.md / AGENTS.md / editor rules",
                "points": 0,
                "status": "missed",
                "details": [
                  {
                    "code": "no_agent_instructions",
                    "params": {}
                  }
                ],
                "max_points": 45
              },
              {
                "key": "machine_readable_docs_llms_txt",
                "name": "Machine-readable docs (llms.txt)",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 15
              },
              {
                "key": "legible_commit_history",
                "name": "Legible commit history",
                "detail": "85 of 85 human commits state their intent (structured subject or explanatory body)",
                "points": 40,
                "status": "met",
                "details": [
                  {
                    "code": "legible_history",
                    "params": {
                      "legible": 85,
                      "sampled": 85
                    }
                  }
                ],
                "max_points": 40
              }
            ]
          },
          {
            "key": "ai_verify_loop",
            "band": "at_risk",
            "name": "Verify loop (build / test / typecheck)",
            "note": null,
            "notes": [],
            "value": 32,
            "inputs": {
              "has_nix": false,
              "has_tests": true,
              "lockfiles": [
                "uv.lock"
              ],
              "has_dockerfile": true,
              "typed_language": false,
              "bootstrap_files": [],
              "has_devcontainer": false,
              "has_linter_config": false,
              "typecheck_configs": [],
              "agent_commit_share": 0,
              "toolchain_manifests": [],
              "dependency_bot_commit_share": 0
            },
            "components": [
              {
                "key": "one_command_bootstrap",
                "name": "One-command bootstrap",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 18
              },
              {
                "key": "automated_tests",
                "name": "Automated tests",
                "detail": null,
                "points": 22,
                "status": "met",
                "details": [],
                "max_points": 22
              },
              {
                "key": "lint_format_config",
                "name": "Lint / format config",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 11
              },
              {
                "key": "static_type_checking",
                "name": "Static type checking",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 11
              },
              {
                "key": "reproducible_environment",
                "name": "Reproducible environment",
                "detail": "Dockerfile, lockfile",
                "points": 10,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "Dockerfile, lockfile"
                    }
                  }
                ],
                "max_points": 10
              },
              {
                "key": "demonstrated_agent_practice",
                "name": "Demonstrated agent practice",
                "detail": "no agent-authored commits among the last 85",
                "points": 0,
                "status": "missed",
                "details": [
                  {
                    "code": "no_agent_authored_commits",
                    "params": {
                      "sampled": 85
                    }
                  }
                ],
                "max_points": 10
              },
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                "key": "automated_maintenance",
                "name": "Automated maintenance",
                "detail": "no automated dependency updates observed",
                "points": 0,
                "status": "missed",
                "details": [
                  {
                    "code": "no_dependency_automation",
                    "params": {}
                  }
                ],
                "max_points": 8
              },
              {
                "key": "openssf_scorecard_pinned_dependencies",
                "name": "OpenSSF Scorecard: Pinned-Dependencies",
                "detail": "dependency not pinned by hash detected -- score normalized to 0",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 10
              }
            ]
          },
          {
            "key": "ai_code_legibility",
            "band": "moderate",
            "name": "Code legibility for models",
            "note": null,
            "notes": [],
            "value": 55,
            "inputs": {
              "primary_language": "Python",
              "largest_source_bytes": 30306,
              "source_files_sampled": 70,
              "oversized_source_files": 0
            },
            "components": [
              {
                "key": "type_checkable_code",
                "name": "Type-checkable code",
                "detail": "Python without a type-check config",
                "points": 0,
                "status": "missed",
                "details": [
                  {
                    "code": "no_typecheck_config_language",
                    "params": {
                      "language": "Python"
                    }
                  }
                ],
                "max_points": 45
              },
              {
                "key": "manageable_file_sizes",
                "name": "Manageable file sizes",
                "detail": "0/70 source files over 60KB",
                "points": 55,
                "status": "met",
                "details": [
                  {
                    "code": "oversized_source_files",
                    "params": {
                      "kb": 60,
                      "sampled": 70,
                      "oversized": 0
                    }
                  }
                ],
                "max_points": 55
              }
            ]
          },
          {
            "key": "ai_interfaces",
            "band": "at_risk",
            "name": "Machine-readable interfaces",
            "note": null,
            "notes": [],
            "value": 40,
            "inputs": {
              "example_dirs": [
                "examples"
              ],
              "has_mcp_signal": false,
              "api_schema_files": []
            },
            "components": [
              {
                "key": "api_schema_openapi_graphql_proto",
                "name": "API schema (OpenAPI/GraphQL/proto)",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 40
              },
              {
                "key": "mcp_server",
                "name": "MCP server",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 20
              },
              {
                "key": "runnable_examples",
                "name": "Runnable examples",
                "detail": "examples",
                "points": 40,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "examples"
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                "max_points": 40
              }
            ]
          }
        ],
        "description": "How well is the repo equipped to be developed and maintained with AI coding agents? An independent, experimental badge — weight 0.0, so it is surfaced on its own and does not affect the overall health score."
      }
    ],
    "metrics_version": "1.13.0"
  },
  "warnings": [
    "Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token",
    "GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository",
    "deps.dev does not index pypi:ragleap-rag@0.6.0; advisories assessed against the repository dependency graph instead"
  ],
  "report_type": "repository",
  "generated_at": "2026-07-26T19:04:40.132295Z",
  "schema_version": "0.27.0",
  "badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/a/antonyrag/ragleap-core.svg",
  "full_name": "antonyrag/ragleap-core",
  "license_state": "standard",
  "license_spdx": "MIT"
}

评分是信号,而非担保。 评分反映的是 GitHub 上公开可见的实践——不是代码审计,也不是安全保证。

缺失数据将被剔除并重新归一化权重,绝不按零分计。方法论已版本化并公开:指标 v1.13.0、模式 v0.27.0—— 完整方法论 · 指标知识库.

单项结果在整体记录中的位置: 汇总统计PyPI.