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dsh-knowledge

Curated pickMaintenance: Active

soren-abt/dsh-knowledge

Knowledge base & RAG plugin for DeepSeek Harness (DSH): chunking, local embeddings, hybrid search, management panel

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$ dsh plugin --profile <name> add dsh-knowledge

30

stars

7

forks

TypeScript

Language

AGPL-3.0

License

2026-08-15

Created

2026-09-16

Last push

Build DSH knowledge bases from files, folders, URLs, and text, then retrieve bounded evidence through `knowledge_search`.

DSH integration

Native runtime

Author-claimed

Safety audit

Unaudited

Last verified

2026-09-08

License

AGPL-3.0

01What can it help you accomplish?

  • Import DSH knowledge sources and retrieve evidence for model use

    Managed knowledge bases with lexical, vector, or hybrid retrieval and ordered evidence context

    DSH users who need local or provider-backed document RAG

02How to install into DeepSeek Harness

Prerequisites

  • Node.js ^22.19.0 || >=24.0.0, pnpm >=10, initialized DeepSeek Harness, and the listed `allowBuilds` permissions.

Installation steps

  1. 01

    Run `dsh plugin --profile <name> add dsh-knowledge`, then restart the Web service and refresh the page.

    $ dsh plugin --profile <name> add dsh-knowledge

Verify the integration

  • Use Recall Test before allowing the model to use the knowledge base through `knowledge_search`.

03DSH integration and capability boundaries

DSH integrationNative runtime

DSH knowledge-base and RAG plugin

  • Knowledge-base management and retrieval

    Files, directories, URLs, or plain textPersisted knowledge bases and 14 model tools including `knowledge_search`

    Permanent deletion requires host confirmation.

04Who is it for? When not to use it?

Good for

  • DSH users who need local or provider-backed document RAG

Not for

  • Intel Macs cannot run onnxruntime-backed local embedding and OCR; use an OpenAI-compatible service or Ollama instead.
  • API keys are stored in plaintext locally; protect the profile data directory.

05Compatibility, maintenance and safety notes

  • Intel Macs cannot run onnxruntime-backed local embedding and OCR; use an OpenAI-compatible service or Ollama instead.
  • API keys are stored in plaintext locally; protect the profile data directory.
2026-08-152026-09-04v0.3.9

AGPL-3.0 source; author README claims captured from the fetched main branch

06Frequently asked questions

Can it work without local embedding models?

Yes. The README says it can run with zero vector configuration; keyword retrieval remains available without downloaded models.

How do I validate retrieval before model use?

Use the Recall Test, then let the model use the base through `knowledge_search`.

What happens when a selected knowledge base is empty or invalid?

The author says it matches zero bases and does not silently expand the search to every base.

08Data and sources

  • Author-claimedgithub.com95e4a135cca3…

    dsh-knowledge 把文档导入、解析、分块、检索、证据组织和模型续读整合进 DSH。它既可以零向量配置运行,也可以完全使用本地模型,不要求额外部署独立的知识库服务。

This page is generated from the project’s public documentation, repository metadata and a structured parse of DSH Plugins; last verified on 2026-09-08. Found an error? Submit a correction.

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