プラグイン

DSH スキンプラグイン。Alphacoders の人気壁紙を DeepSeek Harness Web GUI の背景に設定できます(ギャラリー、検索、ローカル画像アップロード、ライト/ダークマスクに対応)。

テキスト専用の DeepSeek Harness(dsh)モデルにビジョン機能をプラグインとして追加します。低価格/無料の VLM プリセットを内蔵した `vision` ツール、複数画像の一括解析、貼り付けによる画像入力、ホットリロード対応の Web 設定ページを提供します。

/repro コマンドは、最小限で機密情報を除去した再現可能な問題バンドル(セッションログ、失敗したコマンド、Git diff)をエクスポートします。

Google Play store screenshot generator for DeepSeek Harness — /playstoreshots turns an app logo plus two reference sheets into four 1080x1920 screenshots and one 1024x500 feature graphic via Bailian wan2.7-image-pro.

DeepSeek Harness plugin: Aliyun Yunxiao requirements and defects kanban by status, with detail drawer, image preview, one-click session dispatch, Req/Bug creation, and native tools for status transitions, work item creation, project member lookup, change-

A floating VRM avatar with tool-driven expressions and VRMA animations, plus model and motion asset management.

A desktop pet for DSH: a blue whale girl with 104 animations and built-in voice. It is standalone, but its pet runtime is a rework of dsh-dafeiyu — disable the upstream dsh-dafeiyu before installing, or both will run and fight over the control port. Windows x64 only, and the first launch downloads about 580 MB of assets.

Redacts PII in tool-result text before it is logged (error-result metadata is not rewritten), denies read_image and binary/document reads outside allowPaths, provides local privacy_extract, privacy_ocr, privacy_scan and privacy_rehydrate tools (PDF/OCR needs a separately installed local extractor configured through extractCli), and enforces a fail-closed llm/stream egress guard before DSH dispatches any model request.

WeCom smart bot over the official long connection (Bot ID + Secret, no public callback): persona, sender identity tags, three-layer memory with a forgetting curve, reminders, opt-in proactive chat, owner-only work mode guarded by tools.guard, auto-steer, image input and a wecomSoulBot host service; group chats answer when @-mentioned.

Adds an Artifact Space entry to the DSH sidebar that lists the final effective artifacts of each session, grouped by workspace and session, with an editor-style preview, image previews, search across workspaces and sessions, favorites, and provenance for every file.

Local media toolbox for DeepSeek Harness: converts files between 27 video, audio and image formats, trims clips, extracts audio or video tracks without re-encoding, exports embedded subtitles to .srt, compresses images with a before/after preview, reads and rewrites metadata, and encodes or decodes Base64 — all through the ffmpeg already installed on the machine, so files never leave it. The same engine is registered as a media_toolbox tool agents can call.

Per-workspace personal knowledge base for DeepSeek Harness: each identity gets an isolated local library — import PDF, Word, Excel, Markdown, text, HTML and images, auto-chunk and embed into SQLite with FTS5 + vector hybrid retrieval, then ask questions in chat with numbered citations back to the source. Local-first, no cloud upload; vector embeddings need a local Ollama (default bge-m3), and without it retrieval degrades to FTS5 keyword search.

Connect DeepSeek Harness to the local Codex CLI with dynamic model discovery, image input, Harness-owned tools, and read-only ChatGPT plan and quota display.

Local LoRA and QLoRA fine-tuning in a panel: import JSONL, see a VRAM estimate before training starts, evaluate, and export an adapter. One-click Python venv setup, but you must supply your own Python 3.10+ and an NVIDIA GPU (6 GB or more). Verified end to end on Windows 11 with an RTX 3060 6 GB; the installer refuses non-Windows hosts, so Linux, macOS and other GPUs are unsupported for now.

Adds MiniMax open-platform models to the DSH model picker: paste the API key in Settings and MiniMax models become selectable, with the M Plan quota windows shown beside the composer.

Signs in to ima.qq.com (Tencent IMA) with a WeChat QR code and runs a localhost OpenAI-compatible relay in front of its SSE chat endpoint, so the four models behind it appear in the picker.

Animal Island theme with boarding-pass masthead, cream notebook paper, 118 ThemeRuntime tokens, in-app appearance presets, and starry night mode.

Wallpaper layer behind the whole DeepSeek Harness Web UI, fed by image URLs, local files and folders, or a Wallpaper Engine workshop directory, with opacity, blur and translucent-panel sliders, a slideshow with random order and cross-fade, muted video playback, previous/next keyboard shortcuts, and a per-URL archive that keeps every fetched picture under "Loaded images".

Speaks the estimated spend of each turn aloud with an Alipay-style voice clip or a bundled meme voice; amounts come from dsh-cost-meter when installed, otherwise from per-model token prices. All audio is bundled, so nothing is fetched at runtime.

One Settings page for OpenCode Go: an account pool that rotates A-to-B when a key runs out or stops authenticating, per-account 5-hour/weekly/monthly allowance, per-model spend with remaining quota, capability tags (image, video, text-only, tools, reasoning), a live OpenCode-vs-official-API cost comparison, and 10 UI languages.

A DSH workbench for picking photos from local folders on macOS and Windows: local dedupe, filtering and grouping, AI grid triage and scoring with an image-capable model you supply (the plugin bundles no model, credentials or quota), then human review, calibration and export.

Left-sidebar panel that browses the filesystem of the machine the Harness runs on: directory listings with sizes and modification times, text and image previews, file downloads, file uploads into the open directory, and folder creation. The panel speaks twelve languages. Reads and writes run with the privileges of the account that runs the Harness.

Sidebar file explorer for DeepSeek Harness: a lazy workspace tree with in-panel preview for text, Markdown and images, and an action that hands a file to the system default app.

Shows elapsed time, tokens, tokens per second and a shrinking countdown estimate in the chat header for the running turn, and estimates output tokens, context size, cost and duration above the composer before you send.