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dsh-dual-auto

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dsh-dual-auto

Manifest valid

Dual-model auto-routing plugin: low-cost direct / high-cost upgrade with an escape-learning closed loop (wrong direct answers auto-learn fingerprints, force-upgrading the same fingerprint next time),

hasBundlePatch

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

ToolPurpose
dual_model_routeSix-criteria routing decision (length / context / domain coverage / rule conflict / confidence / novelty → six labels). Fingerprints that escaped once are force-upgraded.
dual_model_runDecision + 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_markMark 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

License

MIT

Compatibility

DSH 0.2.2-alpha.2: failedDSH 0.1.6-alpha.2: failedDSH 0.1.7-alpha.2: failed

Versions

Latest versionPublishedSize
0.1.2——
0.1.0——
0.1.1——

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