lengquan88/dsh-dual-auto
双模型 Auto 路由插件：低成本模型直返 / 高成本模型升级 + 逃逸学习闭环（直返答错自动学习指纹，同指纹下次强制升级），状态持久化并与 Python ModelRouter 互通。
这是一个 DeepSeek Harness（DSH）插件。本站汇总其 GitHub README、安装信息、维护状态与公开安全信号。
上游未提供中文 README，当前展示仓库原始内容。
dsh-dual-auto
Dual-model auto-routing plugin for the DeepSeek Harness (dsh).
Low-cost direct / high-cost upgrade with an escape-learning closed loop.
Install
pnpm add @lengquan88/dsh-dual-auto
Enable
Add one row to your profile's cordis.patch.yml:
- insert:
- id: dual-auto
name: '@lengquan88/dsh-dual-auto'
Restart dsh web. The tools dual_model_route, dual_model_run, and
dual_model_mark become available in every session.
Tools
| Tool | Purpose |
|---|---|
dual_model_route | Six-criteria routing decision (length / context / domain coverage / rule conflict / confidence / novelty → six labels). Fingerprints that escaped once are force-upgraded. |
dual_model_run | Decision + real model call: direct → deepseek-v4-flash, upgrade → deepseek-v4-pro (auto-degrade to flash on failure, marked degraded). Probe tasks auto-validate against a gold set — wrong direct answers trigger escape learning. |
dual_model_mark | Mark the quality of a direct result. correct=false learns the fingerprint and rewrites the disk log marker; the same fingerprint is force-upgraded next time. |
Persistence
State persists to output/dsh_router_{fingerprints,stats}.json and
dsh_router_decision_log.jsonl — interoperable with the project's Python
dao/model_router.py (v2 dict fingerprints load directly).
Links
- npm: https://www.npmjs.com/package/@lengquan88/dsh-dual-auto
- Source mirror (atomgit): https://atomgit.com/guaikepa/zhonghua/tree/main/dsh-dual-auto
License
MIT
安全与安装证据
该分数只基于公开仓库元数据与本站登记的安装证据，不等同于代码安全审计。
来自公开插件目录，并链接到公开 GitHub 仓库。
仓库声明 MIT 许可证。
最近 180 天内有代码更新。
尚未登记可复验的精确安装元数据，请按仓库说明手动检查。
已检查的包元数据未声明安装生命周期脚本。