BioDSH

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BioDSH is a one‑click desktop app that puts a bioinformatics agent in front of people who don't use a terminal. Drop in your data, say what you want in plain language, and read the conclusion. It runs locally, never modifies your original files, and can run fully offline inside a hospital or lab intranet.

It is a thin, friendly shell around DeepSeek Harness (dsh): the agent runtime, the plugin system, and the reproducible session log are all dsh. BioDSH adds a clinician‑facing UI, a bioinformatics skill store, a bundled Python analysis environment, and a set of evaluated official skills.

Download

Grab an installer from the latest release:

Platform	File	Notes
Windows 10/11	BioDSH_*_x64-setup.exe	Double‑click to install. On first run click More info → Run anyway.
macOS 12+ (Apple silicon)	BioDSH_*_aarch64.dmg	On first open, right‑click → Open.
Linux	BioDSH_*_amd64.deb	Debian/Ubuntu.

The app checks for new releases in the background and offers a one‑click download → verify signature → install → restart. Nothing is sent anywhere; the update feed is just this repo's latest.json.

What it does

• Everything is a plugin. The best open‑source bioinformatics skills — 2,000+ community skills organised into 10 domains — plus a handful of evaluated, offline, reproducible official skills. Install one with a click.
• Every analysis is traceable. Everything the model sees goes into an append‑only session log. In the chat, intermediate steps fold into a single line and expand on demand; conversations export for an advisor or reviewer.
• Four real example projects ship with the app: single‑cell analysis & plots, literature review, public‑database retrieval, and desktop control with Zotero.
• No coding. A one‑click Python environment (scanpy, anndata, pandas, matplotlib) is bundled; skills that need it install it once.
• Desktop control. The agent can drive other apps (Excel, Prism, SPSS…) with real mouse and keyboard, with a clear "BioDSH is controlling the computer" banner on screen.
• Data safety & offline. Original files are never modified; each analysis writes into a new subfolder. Fully‑offline mode talks to a local or intranet model and makes no outbound requests.

How it works

┌────────────────────────────────────────────┐
│  BioDSH (Tauri desktop shell)               │
│  • clinician‑facing UI (React)              │
│  • skill store · data view · environment    │
│  • bundled Python + official skills         │
│  ┌──────────────────────────────────────┐  │
│  │  DeepSeek Harness (dsh)               │  │
│  │  agent runtime · plugins · session log │  │
│  └──────────────────────────────────────┘  │
└────────────────────────────────────────────┘

A "skill" is a dsh plugin: a folder with a SKILL.md (instructions the agent follows) and optional scripts. The official skills live in biodsh-core/skills/; the desktop app is in desktop/.

Use with vanilla DeepSeek Harness

BioDSH's official skills are ordinary dsh-native SKILL.md skills, so plain dsh picks them up automatically — no BioDSH app required. dsh scans a few skill folders; the simplest is a per-project .agents/skills/:

git clone https://github.com/sagirimo/BioDSH
cd BioDSH
# copy the skills into your dsh project (or run it from inside that project for ./.agents/skills)
./scripts/install-into-dsh.sh /path/to/your/dsh-project/.agents/skills
#   --global  installs into ~/.agents/skills instead

On Windows use scripts/install-into-dsh.ps1. Start dsh from that workspace and the BioDSH skills are available. (The scRNA / plotting skills expect a Python env with scanpy, anndata, pandas and matplotlib on PATH.)

Build from source

Prerequisites: Node.js 22+, Rust (stable), and the platform Tauri prerequisites (on Linux: libwebkit2gtk-4.1-dev libappindicator3-dev librsvg2-dev patchelf).

cd desktop
npm ci                        # install dependencies
node scripts/stage-dsh.mjs    # stage the dsh runtime
node scripts/sync-skills.mjs  # official skills → resources + store catalog
npm run tauri dev             # run the app
# or a full installer build:
npm run tauri build

The release recipe is at docs/release.workflow.yml — copy it to .github/workflows/release.yml, then push a tag such as desktop-tauri-v0.2.1 to build installers for all platforms and publish a release with latest.json. Auto‑update signing needs two repository secrets, documented at the top of that file.

Repository layout

Path	What
desktop/	The Tauri desktop app — React UI (src/), Rust backend (src-tauri/), build scripts (scripts/), store catalog (store/).
biodsh-core/skills/	The evaluated official skills shipped with the app.
desktop/resources/	Bundled resources: the analysis‑environment spec, example‑project sessions, helper scripts.

License

MIT for BioDSH's own code. Bundled and downloaded components — DeepSeek Harness, community skills, the Python toolchain and packages — keep their own licenses.

Acknowledgements

Built on DeepSeek Harness. BioDSH is an independent project and is not affiliated with or endorsed by DeepSeek.