DeepSeek Harness Plugin

Laplace-bit/dsh-smooth-stream

Stars ★ 8 Category UI Enhancements Added 2026-08-16 npm dsh-smooth-stream

Silky streaming reveal for the Web UI: text appears at the model's arrival rate, new lines glide in, no flicker; follow stays with the user and prefers-reduced-motion is respected.

Install

# from npm (prebuilt)

dsh plugin --profile web add dsh-smooth-stream

# from GitHub (first run asks for allowBuilds approval — follow the hint, retry)

dsh plugin --profile web add github:Laplace-bit/dsh-smooth-stream

Any plugin you install runs third-party code with your own permissions — it can read your files, use your credentials, and reach the network, and tool approvals don’t sandbox it. GitHub-sourced plugins also run build scripts at install time. Only install sources you trust, and pin a commit (github:owner/repo#sha).

README

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dsh-smooth-stream is a DeepSeek Harness (dsh) community plugin for silky streaming in the Web UI: arrival-tracking typewriter reveal, glide-in wraps, no flicker. It is not part of the official DeepSeek distribution.

Project homepage: https://laplace-bit.github.io/dsh-smooth-stream/

Preview

Left: default Web UI. Right: dsh-smooth-stream.

Left: without the plugin. Right: with dsh-smooth-stream.

What it does

  • Reveal tracks the model. Assistant text appears at a cadence that follows the arrival rate. Fast bursts do not dump a whole paragraph; a slow stream does not sit still and then jump.
  • Markdown stays markdown. Code, emphasis, and the rest render while the reply is still coming. There is no plain-text tail that later swaps into formatted markdown.
  • Wraps glide in. A new line or a growing tool card eases into view instead of snapping the transcript up by a line.
  • You keep the scroll. Scroll up to read earlier text and the overlay lets go. Follow resumes only when you return to the bottom — the to-bottom button counts.
  • Think stays the built-in row. Reasoning uses the usual disclosure. It opens while thinking is the live tail and closes when thinking ends; the chevron still toggles by hand.
  • The rest of the turn moves with it. Running tool cards, model retries, and workflow runs share the same follow, so the whole turn slides instead of only the assistant text.
  • It backs off when it should. prefers-reduced-motion shows the finished text at once and does not take follow. If the frame rate drops below 30 fps and the reply is off-screen, reveal pauses and catches up when the view is healthy again.

Install

From a DeepSeek Harness source checkout:

pnpm dsh plugin --profile web add dsh-smooth-stream

If dsh is already on your PATH:

dsh plugin --profile web add dsh-smooth-stream

The npm package ships prebuilt lib/, so no pnpm ≥10 build-script allowance is needed.

Start the UI:

pnpm dsh web

The Host log should include [dsh-smooth-stream] plugin loaded!.

Remove it with pnpm dsh plugin --profile web remove dsh-smooth-stream (or dsh plugin --profile web remove dsh-smooth-stream).

Configuration

The bundle installs with preset: balanced. Change it in the profile cordis.patch.yml if you want a different cadence:

preset Feel
realtime Keeps closer to the model
balanced Default
silky More buffer, slower catch-up

maxScrollSpeedPxPerSec (default 1000) is a ceiling so the first large lag does not teleport.

FAQ

Is this an official DeepSeek plugin? No. It is a community plugin for the DeepSeek Harness (dsh) Web UI, MIT-licensed, and not part of the official DeepSeek distribution.

How do I install a DeepSeek Harness plugin? Use the built-in plugin command: dsh plugin --profile web add dsh-smooth-stream from a dsh source checkout (see Install).

Can I install it from npm? Yes — dsh-smooth-stream is published to npm. dsh plugin --profile web add dsh-smooth-stream installs the prebuilt package.

Does it respect prefers-reduced-motion? Yes. With reduced motion enabled the finished text is shown at once and the plugin does not take over follow. If the frame rate drops below 30 fps while the reply is off-screen, reveal pauses and catches up later.

License

MIT

Content from the project README on GitHub ↗

Links

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