starefinger/dsh-llm-qwen-local
面向 DeepSeek Harness(dsh)的 LLM 适配器插件:驱动由 OpenAI 兼容服务的本地部署 Qwen3.8-27B 模型。支持按模型多模态开关、完全可配置的推理档位、请求图像投影,以及中英双语 Web 设置页。
Project Overview项目介绍
A DSH adapter plugin that connects a locally deployed Qwen model (e.g. Qwen3.8-27B) served by vLLM via its OpenAI-compatible endpoint. Core capabilities: a per-model multimodal switch and fully configurable reasoning effort levels. Use it when running Qwen offline or behind a private vLLM server. Caveat: the multimodal declaration is unverified — true on a text-only endpoint fails mid-turn, false on a vision endpoint is silent.
DSH 适配器插件,连接本地 vLLM 部署的 Qwen 模型(如 Qwen3.8-27B)OpenAI 兼容端点。核心能力:每模型多模态开关、推理强度完全可配置。适用于需离线或私有部署 Qwen 的场景。注意:多模态声明不会验证,文本端开启视觉会中途失败。MIT,社区维护。
请帮我安装这个 DSH 插件。安装前先完成【兼容性检查 + 安全性检查】,检查通过再动手。
插件:dsh-llm-qwen-local(starefinger/dsh-llm-qwen-local)
仓库:https://github.com/starefinger/dsh-llm-qwen-local
本站详情页:https://www.yhbd.top/plugins/starefinger-dsh-llm-qwen-local/
本站登记:类型 plugin · 归类 原生 DSH 插件 · 许可证 MIT · ⭐ 4 · 最近提交 2026-09-24 · 主语言 TypeScript
按下面顺序执行,每步先把结论告诉我,再进入下一步:
【1 兼容性检查】
① 我这边:DSH 版本、Node 版本、操作系统、当前 profile(web / desktop)。
② 读它的 README、package.json、插件 manifest,列出它要求的 DSH 版本 / Node 版本 / 操作系统 / 外部依赖 / 需要另外先装的运行时。
③ 逐条比对,结论只写「满足 / 不满足 / 未知」三种;不满足的给出可行替代方案。
④ 检查是否和我已装的插件冲突:命令名重复、skill / tool 重名、端口占用、重复注册的 MCP server。
【2 安全性检查】
① 仓库可信度:和上面「本站登记」是否一致;star / fork 数、创建时间、最近提交,是否归档或长期停更。
② 安装脚本:逐行看 package.json 的 preinstall / install / postinstall,以及 install.sh、setup.ps1 之类脚本。出现 curl|bash、下载后直接执行、混淆代码、访问与插件功能无关的域名,立刻停下来告诉我,不要继续装。
③ 依赖:列出新增依赖,标出无人维护、或与知名包拼写近似的可疑包(typosquatting)。
④ 权限与副作用:它会读写哪些目录、访问哪些域名、需要哪些 DSH 权限(filesystem / network / shell / clipboard 等),以及怎么卸载和回滚。
⑤ 如果它要求 sudo / 管理员权限,或权限明显超出功能所需,先停下来问我。
【3 安装】
上面两步没有「不满足」和「高危项」时才执行;用官方推荐方式安装,不要自行提权。
【4 汇报】
用表格输出:检查项 / 结论 / 依据 / 是否需要我决策。拿不准的一律写「未知」并说明要我怎么确认——不要猜,也不要替我决定。
Send this message to DSH in your current session: it verifies compatibility and security first (answering met / not met / unknown item by item) and only installs once everything checks out — it will stop and ask you if it finds a high-risk item. The box scrolls; the copy is the full prompt. CLI install commands may not be accurate across systems, so DSH is the safer route.把上面这条消息直接发给当前会话里的 DSH:它会先核对兼容性与安全性(逐条给「满足 / 不满足 / 未知」),确认没问题再安装,有高危项会停下来问你。框内可滚动,复制到的是完整提示词;安装命令不一定准确,发给 DSH 更稳。
- Only 4 stars - very few users, little community feedback星标只有 4,几乎没人在用,遇到问题缺少社区反馈
DSH walks through these 9 checksDSH 会逐条核对这 9 项
Compatibility兼容性
- DSH, Node, OS and profile requirementsDSH 版本 / Node 版本 / 操作系统 / profile 是否满足要求
- External dependencies and runtimes (Electron / Python / Docker, ...)外部依赖与运行时(Electron / Python / Docker 等)是否齐备
- Conflicts with installed plugins: command names, skill / tool names, ports, duplicate MCP registration与已装插件是否冲突:命令名、skill / tool 重名、端口占用、重复 MCP 注册
Security安全性
- Repo matches the facts registered here; archived or abandoned?仓库是否与页面登记一致,是否归档或长期停更
- Safety of preinstall / install / postinstall and install.sh / setup.ps1preinstall / install / postinstall 与 install.sh、setup.ps1 是否安全
- curl|bash, download-then-execute, obfuscation, unrelated domains → stop immediatelycurl|bash、下载即执行、混淆代码、无关域名 → 立刻停止
- Typosquatting or unmaintained packages among the new dependencies新增依赖里有没有 typosquatting 或无人维护的包
- Requested permissions vs. what the feature actually needs申请了哪些权限、是否超出功能所需(filesystem / network / shell / clipboard)
- Any sudo / admin requirement, plus uninstall and rollback是否要求 sudo / 管理员权限,以及卸载与回滚方式
Anything uncertain must be marked unknown with a note on how to confirm it. This site's signal screen is a static snapshot, not a security audit.拿不准的必须标「未知」并说明要我怎么确认。本站的信号筛查是静态快照,不能替代安全审计。
Or use CLI install (for developers)或使用命令行安装(适合开发者)
CLI Install命令行安装
dsh plugin --profile web add dsh-llm-qwen-local
把 starefinger/dsh-llm-qwen-local 加入你的 DSH 配置(web profile)即可启用。
READMEREADME
dsh-llm-qwen-local
English | 简体中文

DeepSeek Harness LLM adapter plugin for a locally deployed Qwen model (e.g. Qwen3.8-27B) served by vLLM behind its OpenAI-compatible /v1/chat/completions endpoint.
v0.4.1 · exact compatibility target: DSH
0.1.2-rc.1· MIT · community-maintained and not a DeepSeek or Qwen product.
✨ New in v0.4.1 — settings-page fixes;
maxRequestImageBytesroute cap removed
- No more focus loss while typing a reasoning-effort id (or a model id) — list rows now key off a stable row identity instead of the id text, so typing no longer remounts the row.
- Shorter, uniform field labels — long explanations moved into input placeholders; model-card columns are width-aligned.
maxRequestImageBytes(the per-request total image byte cap) is removed from config, schema, and the settings page. Every image is inlined once it fits its per-image budget (imageMaxPixels/imageMaxBytesare unchanged); an oversized request is refused by the backend LLM service against its own input limits. A leftover value in an existingsettings.yamlis silently ignored — no migration needed.- "Discover models from endpoint" now probes with the key currently in the API Key field — a freshly typed key works without saving first.
- The model list can be emptied —
modelsno longer requires at least one entry: save an empty list and the route stays mounted but dormant (no selectable models), then re-populate via "discover models from endpoint" or a manual add.
✨ New in v0.4.0 — zero runtime
@deepseek-aidependenciesThe published plugin no longer depends on any
@deepseek-aipackage at runtime — noschemastery,dsh-llm,dsh-settings,dsh-attachment,dsh-launch-environment, orcordis. Its only runtime dependencies are the MIT-licensedeventsource-parserand Node.js builtins.Why: the plugin now reproduces every DSH seam it touches (adapter contract, failure snapshots, brand ids, API-key/attribution/launch-env helpers, the settings-namespace
Configsurface) as small local modules undersrc/harness/plus a frozen, hand-owned configuration surface. It loads against the host's live services without importing the packages that define them — the same dependency posture as thedsh-llm-ollamareference implementation.What does not change: external plugin behavior is identical — provider route
qwen-local, settings namespacellm-qwen-local, the settings page, model discovery, and the wire dialect. The DSH compatibility target stays0.1.2-rc.1. The@deepseek-aipackages remain dev-only type pins (theirimport typereferences are erased from the build), so existing installs keep working as-is.Upgrading: drop-in — just
dsh plugin --profile web add dsh-llm-qwen-local@0.4.1(or your pinned snapshot tag). No configuration changes required.
Showing the opening section of the README — the full document lives in the repository以上为 README 开头摘要,完整文档在仓库内 · View the full README on GitHub →在 GitHub 查看完整 README →
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