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DeskNext 0.4.0 Preview 1 · Windows x64 / 开发预览

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@WSXYT WSXYT released this 05 Oct 17:51
v0.4.0-preview.1
936e102

DeskNext 0.4.0 Preview 1 · Windows x64

A working desktop file workspace—with AI suggestions you remain in control of.

English · 简体中文

Unsigned development preview, not a production release. Back up important data and start with a small test folder. This release does not enable unattended file organization.

Download and start

Download DeskNext-0.4.0-preview.1-win-x64.zip below and extract the entire archive to a local folder. For a portable launch, open:

payload/DeskNest.App.exe

Keep the payload directory together; do not copy just the executable. The included runtime does not require an installed .NET SDK or Python. Models are separate and optional.

For a per-user installation, follow the included README.md and Install.ps1. The installer prints the installed application's path. Follow your organization's script policy; no system-wide policy changes are required. Windows may warn because this build is unsigned—verify the download against SHA256SUMS and review the source before deciding to run it.

What to try

  • Create a managed space or map an existing folder; open a space in its own desktop window.
  • Import a file or folder after reviewing its source and destination, then try the recorded Undo action.
  • Use file menus, search, the collection capsule, tray access, list/grid/details views and app-only custom icons.
  • Choose light/dark/system appearance, an accent color, or one of twelve interface languages.
  • Download/install the optional local Laya model in Settings. Verification and a real CPU loading check run before a new model can be selected; save settings to activate it.
  • Preview a classification, add a short clarification when a filename is ambiguous, and explicitly choose/confirm a destination. No model response moves files on its own.
  • Optionally configure Jev with your own key and explicit sending consent. Your entered notes may be sent along with filenames, types and category descriptions; file contents and absolute paths are not automatically uploaded. API usage may be charged.

Recovery and data

Managed deletion moves items to the application's recovery area; removing a mapped reference does not delete its original. Undo refuses changed or insufficiently identified items rather than overwriting them. Outgoing drags request Copy and never delete their sources. Model repair installs a fresh copy and leaves the old directory intact. Application uninstall preserves workspaces, model caches and unknown files.

Scope of this build

This Windows x64 snapshot was installed and exercised with the real CPU worker. Three fixed A–D comparison cases matched preprocessing, rankings and actions within the documented numerical tolerances. A separate installed-app fixture completed model suggestion → explicit confirmation → file import → undo, and uninstall retained its unknown-file sentinel.

That is not a large-sample classification-quality result, GPU validation, clean-machine certification, power-loss guarantee or signing/notarization acceptance. Local previews currently cold-start a worker. Live Jev evaluation, model removal/cache maintenance, broader automation/Flow and remaining release work are still open. macOS/Linux source builds have separate evidence; this asset contains only Windows x64 binaries.

Build identity: 0.4.0-p4-parity-20261005, application source snapshot 936e102. The archive is renamed for readability; its bytes are unchanged from the checked development bundle.

SHA-256:

2ed4a34b729fd9a619da178211fd47d105f5ec8651efd7a1aa52971749a14b01

Project / build guide · Model package · Detailed coverage · Report an issue

简体中文

可以开始体验的桌面文件工作区：AI 提供建议，每一次移动仍由你确认。

这是未签名的开发预览版，不是正式发行版。请备份重要数据，先用少量测试文件体验。当前不启用无人值守自动整理。

下载与启动

下载下方 DeskNext-0.4.0-preview.1-win-x64.zip，完整解压到本地文件夹，打开 payload/DeskNest.App.exe 即可便携运行。请保留整个 payload 目录，不要只复制主程序。运行时不需要安装 .NET SDK 或 Python，模型独立下载且不是手动整理的前提。

如需按用户安装，请按压缩包内的 README.md 运行 Install.ps1，安装器会给出启动路径。遵守所在组织的脚本策略，不需要修改系统全局策略。由于未签名，Windows 可能提示风险；请核对 SHA256SUMS 并审阅来源后自行决定是否运行。

建议体验顺序

  1. 新建托管空间或映射已有文件夹，再打开独立空间窗。
  2. 拖入文件/目录，核对来源和目标后确认导入，再体验操作历史中的撤销。
  3. 使用搜索、收集箱、托盘、排列方式、自定义图标与主题色；界面支持十二种语言。
  4. 在设置中下载或离线安装 Laya 模型，等待校验与 CPU 加载检查，保存设置后启用。
  5. 请求分类建议；文件名不清楚时补充简短说明，再手动选择并确认目标。模型本身不会执行文件移动。
  6. 如需 Jev，可填写自己的密钥并明确同意发送。可选补充说明会与文件名、类型、分类说明一起发送；不自动读取或上传正文和绝对路径，API 可能收费。

数据与限制

托管删除进入应用恢复区，移除映射引用不删除原文件；身份不足或内容变化时撤销会拒绝覆盖。外拖只请求复制，不删除源文件。模型修复生成新副本，保留旧目录；卸载应用也会保留工作区、模型缓存和未知文件。

本包已通过安装版 CPU worker 的三个固定案例 A–D 对照，以及独立的“建议 → 明确确认 → 导入 → 撤销”文件流程和卸载保留文件检查。这不代表大样本分类质量、GPU、干净机、掉电耐久性或签名验收。Jev 实际评测、模型清理、自动化/Flow 和其余发行工作仍在推进。当前附件仅供 Windows x64；macOS/Linux 的源码与证据分别维护。

构建标识为 0.4.0-p4-parity-20261005，源码快照与 SHA-256 见上方。详情见中文 README，问题请提交到 Issues，不要附带私人文件、密钥或未脱敏的恢复记录。

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