Bazley13/dsh-multi-model-orchestrator1

dsh-multi-model-orchestrator

A DeepSeek Harness (dsh) plugin: orchestrates complex tasks across multiple models — a 'main brain' decomposes the task and dispatches subtasks to GLM / Kimi / Qwen etc. sub-agents by each model's strengths, with per-model token usage.

AI 分析

核心用途是多模型协同任务编排,将复杂任务拆解并分发给最擅长的模型。适合需要混合使用多种国产/外置大模型进行复杂工作流处理的开发者和高级用户。

パッケージ
dsh-multi-model-orchestrator
バージョン
0.2.2
ライセンス
MIT
最終更新
2026/09/07

インストール

$npx -p @deepseek-ai/dsh dsh plugin --profile web add github:Bazley13/dsh-multi-model-orchestrator

ドキュメント

README 全文を読む ↗

Configuration reference

Everything is configured in $DSH_HOME/settings.yaml:

SectionPurpose
llm-pi-ai.providersOpenAI-compatible third-party model routes (any vendor).
subagent-model-selectionAllow-list of {provider, model} the sub-agent tool may dispatch to.
multi-model-orchestrator.modelNotesPer-route strengths/weaknesses that guide assignment.

To add your own vendor, extend llm-pi-ai.providers with { api, baseURL, apiKeyEnv, models } (any OpenAI-compatible api: openai-completions gateway works), then add matching entries to subagent-model-selection.allowedModels and multi-model-orchestrator.modelNotes.