ningbainb/deepseek-harness-desktop
Open-source Windows desktop client and GUI for DeepSeek Harness — zero-setup installer with Codex, plugins, skills, SSH, mobile remote access, and 11 skins.
DeepSeek Harness Desktop – What It Is
DeepSeek Harness Desktop is an open‑source, cross‑platform desktop application that bundles the DeepSeek AI‑coding runtime (DSH) with a full‑featured IDE‑like interface. It lets you chat with large language models, run code‑editing tools, manage Git repositories, and automate tasks – all from a native Windows, macOS, or Linux client.
Key Capabilities
| Feature | What It Does |
|---|---|
| AI‑powered coding assistant | Chat with DeepSeek (and other) LLMs, get code suggestions, refactorings, and explanations. |
| Integrated file explorer & editor | Browse project files, preview Markdown/HTML/PDF/Office, edit code, and see diffs. |
| Git/SCM support | Visual branch graph, stage/unstage/discard changes, commit history, and remote operations. |
| Skills & plugin ecosystem | Install community‑made Skills (pre‑built toolkits) and plugins directly from the built‑in marketplace. |
| Agent‑based task automation | Define multi‑step workflows; the desktop can dispatch subtasks to “assistant agents” and track results on a Kanban board. |
| Remote development | SSH, SFTP, port‑forwarding, web terminal, and even phone‑based remote control via QR code. |
| Desktop‑only niceties | Themes/skins, a “desktop pet” mascot, tray‑icon/minimize‑to‑tray, and customizable window layouts. |
| Usage dashboard | Real‑time token counts, latency, cache hit‑rate, and cost tracking for each model. |
| Privacy‑first defaults | No telemetry unless enabled; local storage of credentials, no upload of conversation content. |
Platforms & Packaging
- Windows 10/11 x64 – installer includes Node.js, the DSH runtime, Git, and required native binaries.
- macOS Apple Silicon (arm64) – Preview – distributed as a signed DMG/ZIP (not notarized).
- Linux x64 – Preview – available as AppImage and DEB packages; requires system‑installed Git.
All builds are released under the permissive BSD‑3‑Clause license.
How It Works
- Runtime – The app ships the official
@deepseek-ai/dshruntime (currently0.2.0‑rc.2). - Web UI – A bundled web UI (the “Harness Surface”) runs inside an Electron‑style window, providing the chat, file explorer, and plugin UI.
- Desktop Host – A thin native host manages the runtime, installs plugins, handles updates, and isolates the web view from the OS.
- Extensions – Users can add Skills (project‑level, DSH‑bundle, or community‑provided) and third‑party plugins that expose new tools to the AI.
- Automation – Tasks are represented as Kanban cards; when executed, the desktop launches a DSH Agent session, records the run, and stores evidence for later review.
Who Might Use It?
- Developers who want an “AI‑first” IDE without configuring Node, Python, or Docker manually.
- Teams that need a shared AI‑coding environment with Git integration and remote‑SSH access.
- Power users interested in chaining LLM‑driven agents, custom skills, or automating repetitive dev‑ops work.
Getting Started
- Download the appropriate installer from the Releases page.
- Run the installer – it sets up the DSH runtime and a bundled Git client (Windows only).
- Launch DeepSeek Harness Desktop; the first run will guide you through model authentication (e.g., DeepSeek bai login).
- Explore the built‑in Skills marketplace or add your own plugins via the Extensions pane.
- Use the Task Board to create, schedule, or run automated workflows.
Community & Support
- Official QQ group (ID 1105158177) for usage tips, plugin sharing, and troubleshooting.
- The repository includes extensive docs: installation guides, upgrade/rollback procedures, privacy policy, and changelogs.
- Contributions are welcome under the BSD‑3‑Clause license.
In short: DeepSeek Harness Desktop turns the DeepSeek AI‑coding platform into a self‑contained desktop workbench, offering code‑centric LLM chat, file management, Git, remote dev, and extensible automation—all while keeping data local and respecting user privacy.
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