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