dsh-local-ai

dsh plugin --profile web add dsh-local-ai

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🤖 dsh-local-ai

• 1024 store channel: npm i -g dsh1024 once, then dsh1024 plugin --profile web add dsh-local-ai (counts toward the deepseek1024.com install ranking).



Local-model (Ollama) integration for DeepSeek Harness.

Discover, pull, remove, and inspect local models, route requests to them by task type or keyword with automatic fallback to the cloud, and get a one-shot status overview via /ollama.

Official repository. This is the only official repository of dsh-local-ai, maintained by PerryLink. Same-name repositories under other accounts are not affiliated.










[English](README.md) · [简体中文](README-zh.md) · [Español](README-es.md) · [Português](README-pt.md) · [हिन्दी](README-hi.md)

dsh plugin --profile <name> add dsh-local-ai

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📖 Ecosystem knowledge base — measured data, not marketing: plugin development guide · plugin-selection data · maintenance criteria.

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Install & uninstall

• git channel (latest main): dsh plugin --profile web add github:PerryLink/dsh-local-ai — the prepare script builds with production dependencies only.
• npm channel (published releases): dsh plugin --profile web add dsh-local-ai.
• tarball channel: pnpm pack in this repo, then dsh plugin --profile web add ./dsh-local-ai-<version>.tgz.
• uninstall: dsh plugin --profile web remove dsh-local-ai (or remove the row from the profile patch).

If pnpm reports ERR_PNPM_IGNORED_BUILDS for this package, add allowBuilds: { esbuild: true } to your pnpm-workspace.yaml — the dsh CLI prints the exact snippet.

⭐ 如果它帮到了你

这个插件是 DSH 插件家族的一员（95 个，全部 Apache-2.0）。如果你在用，给个 star —— 它不会解锁任何功能，但会让下一个人在搜索里更容易找到它。

English: part of a 95 plugin family for DeepSeek Harness. If it is useful, a star helps the next person find it — nothing is gated behind it.

What is dsh-local-ai?

Local-model (Ollama) integration for DeepSeek Harness.

Discover, pull, remove, and inspect local models, route requests to them by task type or keyword with automatic fallback to the cloud, and get a one-shot status overview via /ollama.

Workflow overview: call → plugin → result. The examples below use the real command surface.

Compatibility

Surface · Status

Harness · DeepSeek Harness dsh-v0.2.1-alpha.1 (verified 2026-10-04: three typecheck rulers (installed, CI, checkout) + 142 tests + self-contained/artifacts gates; the 0.1.7 content-block union is adapted — a tool result is a first-class tool-role message, and a pre-0.1.7 tool-result wrapper is still read for old logs). The peer range admits every supported line: >=0.1.2-rc.1 <0.2.0 \ · \ · >=0.1.5-alpha.1 <0.2.0 \ · \ · >=0.1.6-0 <0.2.0 \ · \ · >=0.1.7-0 <0.2.0 \ · \ · >=0.2.0-0 <0.3.0 \ · \ · >=0.2.1-0 <0.3.0; dev/test pins are 0.2.0-rc.2.

Node · ^22.19.0 \ · \ · >=24.0.0

Backend · Ollama (local HTTP API + CLI probe)

Model · Text-only route (inputModalities: ['text']); tool calls and tool results are supported

What you get

dsh-local-ai makes Ollama a first-class local provider in DeepSeek Harness:

• Discovery & management — ollama_list (installed models, running models, disk usage), ollama_show (parameter size, quantization, context length), ollama_pull, and ollama_remove.
• Health check — process liveness (via the ollama CLI) and API responsiveness (via /api/version), reported as two independent signals.
• Official adapter — the ollama provider route is registered through ctx.llm.registerAdapter (LlmAdapter), with configurable model mapping and temperature / max-tokens / stop translation.
• OpenAI-compatible backends — LM Studio, vLLM, and llama.cpp --server each register as their own openai:<name> provider through the same LlmAdapter seam, reusing one OpenAI /v1/chat/completions adapter (text-only route).
• Local routing — model_route rules route requests to a local model by task type (purpose), case-insensitive keyword, or always, with automatic fallback to the cloud when the local route fails before producing content.
• /ollama command — a one-shot status overview: models, disk usage, health, and suggestions.
• Zero dependencies, HTTP first — everything talks to Ollama's HTTP API (the CLI is used only for the process probe); no model files are bundled.

request (loop)
  

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