2026年10月开源月报：Rust创意工具崛起与AI代理生态繁荣

收录数按本期首次达标收录的项目统计。 本期最早收录记录为 2026/10/9 11:44:24，更早时段没有保存的收录记录。

• storytold/photocraftRust · 75,583 Stars

  图像编辑、PSD编辑

  Stars 统计更新于 2026/11/1 10:21:05

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  作者描述

  PhotoCraft: An open-source, photo editor written by scratch in pure Rust

  编报时的 AI 中文解读

  PhotoCraft 是一款用纯 Rust 编写的开源照片编辑器，旨在重新实现 Adobe Photoshop 的核心功能，支持图层、蒙版、调整图层、图层样式、文字、矢量、画笔以及真实的 PSD 文件。它适用于熟悉 Photoshop 的用户，提供原生应用体验，支持离线使用。

  编报时的 README 依据

  <b>Image editing; an open-source, clean-room reimplementation of Adobe Photoshop, rebuilt in pure Rust.</b><br> Layers, masks, adjustment layers, layer styles, type, vectors, brushes and real PSD files,<br> in a native app written entirely in Rust. Open source, offline, and yours. </p> <p align="center"> <img alt="100% Rust" src="https://img.shields.io/badge/100%25-Rust-b7410e?style=flat-square&logo=rust">

  Open, edit and save layered Photoshop documents. Re-saving keeps the render of 307 of the 309 psd-tools test files. </td> <td width="25%" valign="top"> <h3>🤖 Agent-ready</h3> Every action is a command, so you can drive the same engine from the UI, the CLI, a JSON control channel or an MCP server. </td> </tr> </table> <br> ## Features Every screenshot here is the real app at work on public-domain art, rendered offscreen through its control channel. <table> <tr> <td width="50%" valign="top">

  Every menu item, tool and dialog runs a command from one registry of 500+ commands. The UI, the CLI, the JSON control channel and the MCP server all call the same commands, so anything you can click, a script or an AI agent can do too. ```sh # Headless: open, edit, save photocraft-cli run wave.psd \ --cmd filter.sharpen.smartSharpen --params '{"amount":80}' \ --cmd layer.newAdjustmentLayer.curves --params '{"points":[[0,0],[64,48],[192,212],[255,255]]}' \ --out wave-final.png # Apply one action list to a folder of images

  photocraft-cli batch --actions grade.json --in ./raw --out ./graded # Every subcommand explains itself photocraft-cli batch --help # Let an agent drive it over MCP (headless, or bridged to the running app) photocraft-cli mcp ``` The desktop app also offers an authenticated, loopback-only control channel (`photocraft --control`) for inspecting UI state, driving tools with pointer events, and taking offscreen screenshots. Every image in this README was rendered that way. See [`docs/control-protocol.md`](docs/control-protocol.md). ## Under the hood

  <img alt="macOS · Windows · Linux · FreeBSD · Web" src="https://img.shields.io/badge/macOS%20%C2%B7%20Windows%20%C2%B7%20Linux%20%C2%B7%20FreeBSD%20%C2%B7%20Web-native-2f7bf5?style=flat-square"> <img alt="License: MIT OR Apache-2.0" src="https://img.shields.io/badge/license-MIT%20%2F%20Apache--2.0-3a3a3a?style=flat-square"> <img alt="Status: early alpha" src="https://img.shields.io/badge/status-early%20alpha-d69e2e?style=flat-square"> <br>

  - **Clean-room:** implemented from public specs and observed behaviour only. No proprietary code, shaders or assets. - **Tested:** more than 1,700 tests, including PSD round trips, synthetic generators, compositor oracles and multi-depth checks. ## Get started ```sh git clone https://github.com/storytold/photocraft cd photocraft cargo run --release -p photocraft -- image.psd # the desktop app cargo test --workspace # the test suite ```

  Installers for macOS, Windows, Linux, FreeBSD and the web are attached to each [GitHub release](https://github.com/storytold/photocraft/releases). On Linux you can pick an AppImage, a `.deb`, an `.rpm`, a tarball or a Flatpak bundle. The bundle needs the freedesktop runtime from [Flathub](https://flathub.org/setup), which `flatpak` offers to install along with it: ```sh flatpak install --user photocraft-<version>-linux-x86_64.flatpak # or -linux-aarch64 flatpak run ai.storyteller.photocraft ```

  Maintainers: [`docs/releasing.md`](docs/releasing.md) explains how releases are built, signed and published. > [!IMPORTANT] > **Status:** PhotoCraft is in early alpha, and we want to be straight about where it stands: much of Photoshop's feature surface exists in some form, but **it is not yet a Photoshop replacement for daily professional work**. The biggest gaps are AI/generative features, 15 missing tools, depth in typography and pro workflows, and plug-in compatibility. Every Photoshop menu item is wired to a command ([`docs/parity-checklist.md`](docs/parity-checklist.md)), but that

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• Niko1221/StrataC++ · 37,103 Stars

  模型本地部署、模型接口服务、聊天辅助

  Stars 统计更新于 2026/11/1 10:05:50

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  作者描述

  Qwen3.8-Flash-Next on any consumer hardware: one-click install for Windows / Linux. Strata inference engine, OpenAI/Anthropic API on localhost, optional image input.

  编报时的 AI 中文解读

  Strata 是一个本地运行 AI 模型的桌面和终端应用，支持聊天、编程和图像处理。它提供一键安装，能在消费级硬件上运行某些模型，并通过 OpenAI/Anthropic 兼容 API 连接多种工具。适合想在自有电脑上使用 AI 的用户。

  编报时的 README 依据

  <p align="center"> <picture> <source media="(prefers-color-scheme: dark)" srcset="apps/host/public/brand/strata-lockup-dark.svg"> <img src="apps/host/public/brand/strata-lockup-light.svg" alt="Strata" width="340"> </picture> </p> <h3 align="center">Run powerful AI on your own computer.</h3> <p align="center">Chat, code and work with images, locally.</p> <p align="center"> <a href="#models">Models</a> · <a href="#install"><b>Install</b></a> · <a href="#hardware">Hardware</a> · <a href="#tools">Tools</a> · <a href="#help">Help</a> · <a href="#support-strata">Support</a> </p>

  <a id="using-it"></a> ## Tools **Claude Code · Codex CLI · OpenCode · oh-my-pi · pi.dev · Hermes Agent · OpenClaw**, and more through the OpenAI- and Anthropic-compatible APIs. Run **`strata connect`** to see setup instructions for your tool. [Connection guide](docs/TERMINAL_LAUNCH.md#connect-your-apps-strata-connect). <a id="guides"></a> <a id="how-fast-is-it"></a> <a id="how-does-it-work"></a> <a id="something-went-wrong"></a> ## Help [All guides](docs) · [Troubleshooting](docs/TROUBLESHOOTING.md) · [Report a bug](https://github.com/Niko1221/Strata/issues/new/choose) ·

  <p align="center">_{<b>English</b> · <a href="README.zh-CN.md">简体中文</a> · <a href="README.ja.md">日本語</a> · <a href="README.de.md">Deutsch</a> · <a href="README.fr.md">Français</a> · <a href="README.es.md">Español</a> · <a href="README.pt-BR.md">Português</a> · <a href="README.pl.md">Polski</a>}</p> **Free, open source, and yours to run.** Use Strata on your desktop or with your favorite coding tools. No account needed. ## Models We recommend **ISTA-DASLab first**, then **Unsloth** and other providers, where a compatible model fits. <details>

  **[Download Strata for Windows, Linux or Mac →](https://github.com/Niko1221/Strata/releases/latest)** Install the app, choose a model, and start chatting. There is one installer for each system. On first start the app downloads the engine for your graphics card. [Help with the installer](docs/INSTALL.md#the-app). _{Files: `Strata-0.2.8-windows-x64-setup.exe` · `Strata-0.2.8-linux-x86_64.AppImage` · `Strata-0.2.8-macos-arm64.dmg`} <p align="center"> <img src="docs/media/app-chat.png" width="900" alt="Strata desktop app with a chat and live code preview side by side">

  <br>_{Chat, files and a live preview in one window.} </p> <a id="option-b-the-terminal-one-line"></a> ### Terminal app Prefer the terminal? Install Strata, then run **`strata launch`**. <details open> <summary><b>Install commands</b></summary> **Linux / Mac** ```sh curl -fsSL https://github.com/Niko1221/Strata/releases/latest/download/install.sh -o install.sh && sh install.sh ``` **Windows PowerShell** ```powershell irm https://github.com/Niko1221/Strata/releases/latest/download/install.ps1 | iex ``` On Windows, open a new terminal afterwards. Then: ```sh strata launch ```

  <summary><img src="docs/media/models/deepseek.svg" width="22" alt="" align="middle"> &nbsp;<b>DeepSeekV4.1-Flash-1017</b></summary> In the **desktop app** and the **Terminal**. What does not fit in memory is read from your SSD, so it needs a lot of free disk space. | Set (IST-DAS) | Download | Free disk needed | | --- | ---: | ---: | | 1.75 bpw | 239 GB | about 245 GB | | 2.00 bpw | 257 GB | about 265 GB | | 2.25 bpw | 274 GB | about 280 GB | Runs on NVIDIA RTX 30, 40 and 50 series (Windows and Linux), AMD Radeon AI PRO R9700 (Linux), AMD Ryzen AI Max — Strix Halo

  | **NVIDIA GeForce RTX 20 / 30 / 40 / 50 series** | [NVIDIA setup](docs/INSTALL.md#what-you-need) | | **AMD Radeon RX 7700 / 7800 / 7900, RX 9060 / 9070, AI PRO R9700** | [AMD setup](docs/AMD_HIP.md) | | **AMD Radeon RX 6800 / 6900 · experimental** | [RX 6000 setup](docs/AMD_HIP.md#rdna2-gfx1030) | | **Intel Arc · Linux** | [Intel setup](docs/INTEL_ARC.md) | | **Apple Silicon · M1 or newer** | [Mac setup](docs/MAC.md) | | **AMD Ryzen AI Max · Strix Halo** | [Strix Halo setup](docs/STRIX_HALO.md) | | **NVIDIA DGX Spark · Linux** | [DGX Spark setup](docs/DGX_SPARK_LINUX.md) |

  (Windows), and Apple Silicon Macs with 64 GB or more, text only ([Mac](docs/DEEPSEEK_MAC.md)). Setup downloads the files and the DeepSeek engine, then starts the model. ```sh strata launch --family deepseek41 --model ist-das-2.00bpw --plan ``` Measured with the 2.00 bpw set on Strata 0.2.5 (Strix Halo: 0.2.7). Output is the speed of the answer, prompt is how fast Strata reads your input. | Hardware | Output | Prompt | | --- | ---: | ---: | | RTX 5070 12 GB, 64 GB RAM | 4 to 6 tokens/s | about 110 tokens/s (4K) | | RTX 3060 12 GB, 46 GB RAM | 9 to 11 tokens/s | about 155 tokens/s (4K) |

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• NandhaKishorM/layaPython · 34,772 Stars

  文本决策、多语言分类、模型微调

  Stars 统计更新于 2026/11/1 09:31:00

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  作者描述

  Non-autoregressive System 1 decision engine. Typed choice, score and yes/no decisions over any text in a single forward pass, in 100+ languages, with a router that picks the right checkpoint per request.

  编报时的 AI 中文解读

  Laya 是一个多语言、非自回归的决策引擎，通过单次前向传播对文本进行类型化决策（选择、评分和是/否），支持100多种语言，并配备路由器为每个请求选择最佳模型。它可用于分类、紧急程度评估、客户流失风险预测等场景，适合需要快速、高效决策的应用。

  编报时的 README 依据

  router = Router() # downloads a checkpoint on first use; Router(preload=True) loads all three up front state = "Hi, we were billed twice for March. Please refund the duplicate today or we will cancel our plan." questions = { "department": {"type": "choice", "instructions": "Which department should handle this?", "criteria": {"billing": "invoices, payments, refunds", "technical": "bugs, outages, system errors", "other": "everything else"}},

  Installing the package also installs a `laya` command for quick local testing, no script needed: ```bash laya "I was charged twice, please refund" # routing decision only; works offline, no download laya "Refactor this service" --predict # full answers (downloads the checkpoint on first use) laya "Mein Konto wurde zweimal belastet" --lang de # force a language instead of detecting it laya "My payment failed twice" --lang-guess en # a soft hint: nudge routing, still fall through to detection

  For TypeScript / Node.js / browser, see [`laya-ts/`](https://github.com/NandhaKishorM/laya/tree/main/laya-ts/). npm releases (`npm install laya-ts`) are published from this repository's `laya-ts-v*` release tags. **Long documents.** `laya-multilingual` reads up to 8,192 tokens with `max_len=8192`. Measured accuracy and time by document length, reproducible with [`research/scripts/bench_long_context.py`](https://github.com/NandhaKishorM/laya/blob/main/research/scripts/bench_long_context.py): <p align="center">

  Python 3.10 or newer. Optional extras: `laya[serve]` (HTTP server), `laya[mcp]` (MCP server), `laya[langchain]` (LangChain and LangGraph), `laya[llamaindex]` (LlamaIndex selectors), `laya[crewai]` (CrewAI routing), `laya[onnx]` (ONNX Runtime), `laya[fast]` (TileLang GPU fast path), `laya[structured]` (pydantic models in `decide`). Step-by-step setup for each platform, CPU-only or GPU PyTorch builds, and troubleshooting are in [Installation details](#installation-details).

  > In the table above, 16 to 18 of 20 requests were answered correctly with up to about 4,000 tokens of text before them; beyond that results vary (8 to 17 of 20), so check long-document accuracy on your own data. Short inputs give identical answers with `max_len=8192`, and speed follows the input's real length, not the limit: short inputs are unchanged, and a 4,000-token input takes about 1.7 s on an Apple GPU. Name the checkpoint with `model="multilingual"`, since long mostly-English text would otherwise route to the English checkpoint. ```python from laya import Router

  selected checkpoint, then reuses the Hugging Face cache. Set `HF_HUB_CACHE` to move that cache. The English and typed-decisions checkpoints have about 421M parameters each; multilingual has about 322M (see the table above). Download sizes also depend on weight precision and files. - **Memory limits:** `Router()` keeps up to two checkpoints resident by default (`max_loaded=2`), evicting the least recently used when needed. Use `Router(max_loaded=1)` to reduce resident memory, at the cost of reloads when switching checkpoints. `Router(preload=True)` loads all

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• browser-use/jev-ultrafastPython · 23,993 Stars

  网页自动化

  Stars 统计更新于 2026/11/1 10:20:57

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  作者描述

  Fastest and cheapest web agent

  编报时的 AI 中文解读

  Jev Ultrafast 是一个网页自动化代理，通过动态索引操作空间，让用户用自然语言目标驱动浏览器执行点击、输入等操作，适用于快速完成网页任务。

  编报时的 README 依据

  cp .env.example .env # Add TYPESAFE_API_KEY and TEXT_MODEL_API_KEY. uv run jev ``` Open **http://127.0.0.1:8766** and click **Start demo → Run automatically**. The inspector shows numbered elements, operation probabilities, target probabilities, and executed actions. **Choose next** pauses before execution. Chrome connects through [Browser Harness](https://github.com/browser-use/browser-harness), installed by `uv sync`. Run `uv run browser-harness --doctor` if it needs connecting. Allow remote debugging in Chrome when prompted.

  `TEXT_MODEL_API_KEY` is an OpenRouter key in the example configuration. The current demo uses `inception/mercury-2.5` with reasoning disabled. Gemini, GLM, and DeepSeek can also use the OpenAI-compatible text helper; configure the appropriate model, endpoint, and reasoning setting. ## Use the library ```python from jev_ultrafast import Agent with Agent( "https://www.google.com/travel/flights?hl=en", "Find one-way flights from Zurich to London on September 20, 2026, " "for one adult in economy. Stop when matching flight options are visible.", ) as agent:

  A `DONE` choice still requires independent outcome verification. The DOM reader handles common HTML and ARIA controls, not the full accessible-name specification. Shadow roots, frames, canvas, uploads, pop-up tabs, nested scrolling, and arbitrary keyboard widgets remain outside this MVP. Owned tabs share the existing Chrome profile. ## Development ```bash uv run ruff check . uv run pytest node --check jev_ultrafast/static/app.js node --check jev_ultrafast/snapshot.js uv build ```

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• robbietilton/CompositorSwift · 18,282 Stars

  图像编辑、PSD导入、图像合成

  Stars 统计更新于 2026/11/1 10:20:55

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  作者描述

  The Photoshop alternative for Mac

  编报时的 AI 中文解读

  Compositor 是一款面向 macOS 的免费开源图像编辑器，旨在作为 Adobe Photoshop 的替代品，主要面向需要合成和后期处理工作流的用户。它提供了图层、蒙版、调整层、滤镜、选择工具、绘图和修图等功能，并支持 Photoshop PSD 文件导入。

  编报时的 README 依据

  # Compositor Adobe Photoshop costs too much and tools like GIMP don’t feel familiar enough for me to stay in flow. That’s why I built Compositor. The goal was to create a full-featured image editor that is completely free and open source. I used to use Photoshop for compositing and post-processing, so Compositor is built around that workflow - with the tools needed to create a pixel-perfect final image. Because it’s open source, you can download the Xcode project and add, remove, or modify any feature to fit your workflow. ## Installation ### Download

  - Import JPEG, PNG, HEIC, TIFF, WebP, SVG, PDF (every page its own layer, at 300 DPI or fitted to the canvas), animated GIF (one layer whose frames show in a strip under the canvas, to play, paint on, duplicate, delete and retime), camera RAW (with a develop step first) and Photoshop PSD and PSB (8-bit RGB; not CMYK). Each Photoshop artboard opens in a tab of its own; folders, masks, blend modes, fill rectangles/ellipses, and simple horizontal text stay editable; other vectors and vertical text become pixels. A conversion report is shown before anything is applied.

  Get Compositor from [robbietilton.com/compositor](https://robbietilton.com/compositor), or download the latest release directly from [GitHub Releases](https://github.com/robbietilton/Compositor/releases/latest). ### Homebrew ```sh brew install --cask robbietilton-compositor ``` ## Features ### Layers - Layers and folders, with opacity and Photoshop's full set of blend modes in its order — a folder's opacity dims everything inside it

  trimmed to its pixels; Copy Merged - Keep working while a project saves - Photoshop-style keyboard shortcuts throughout, remappable in Edit > Keyboard Shortcuts - Drag a number's label to scrub its value, as in Photoshop - Automatic updates, signed and notarized ### Works with AI agents - AI agents and scripts can build and edit projects directly: a `.comp` is a folder of PNG layers and a manifest, and an open project updates live as it's written. See [Writing Compositor projects](docs/writing-comp-files.md) ## Requirements - macOS 26.0 or later on a Mac with Apple silicon

  - Xcode 26 or later (to build from source) ## Translations Compositor is English only for now, and translation pull requests aren't being accepted. It's maintained by one person, every new string would need translating from then on, and translations in languages I don't read can't be reviewed. I'll revisit this once the app settles; until then, please don't open localization PRs. ## Other platforms Compositor is macOS only. These unofficial ports are made by others, not reviewed or supported by me, so please report issues to them:

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• openai/mathLean · 17,201 Stars

  数学研究资料、形式化证明

  Stars 统计更新于 2026/11/1 10:25:49

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  编报时的 AI 中文解读

  该仓库包含由未公开的OpenAI内部模型生成的数学手稿和配套的证明工件，作为模型评估的一部分，用于解决开放研究问题。适合数学研究者、形式化验证社区以及关注AI在数学领域应用的读者。

  编报时的 README 依据

  The current catalogue contains 721 manuscripts organized into 373 families. A family groups related papers, which may include a principal result, companion arguments, consequences, or alternative proofs. Each family is classified by mathematical discipline. - Start with the [overview](overview.pdf) for descriptions of the families. - Use the [manuscript map](CONTENTS.md) to find individual papers and their supporting materials. - The [`preprints/`](preprints/) directory contains PDFs, source files, and manuscript-specific citation and build instructions.

  - The [Lean library](lean/README.md) and [formalization catalogue](lean/formalization.yaml) describe the available formal proofs, their associated papers, and verification configurations. See the [Comparator instructions](lean/ComparatorChallenges/README.md) for additional checking instructions. The repository has ~42% top-line results formalized. - Updates to the repo are described in the [history](history.md). ### Reasoning summaries We are also releasing abridged summaries of the model's reasoning, covering the following results: | Family | Subject | |---|---|

  Some of the unformalized results could have issues. We will endeavor to fix any such issues quickly. We are also exploring community-hosted repositories for these materials. In our view, these manuscripts are best understood as a form of raw research data, rather than polished academic papers. We defer to the math community completely on matters of credit, precedence, and concurrent work. ## Navigating the collection

  # Readme This repository contains mathematical manuscripts and supporting proof artifacts produced by an unnamed internal OpenAI model. As part of model development, we evaluate our models on open research problems. We expanded these evaluations after performance on our existing mathematical evaluations saturated. Some outputs build upon earlier results produced by the models. This collection includes results at different stages of verification. Not all have accompanying Lean formalizations. We will continue to update this repository with Lean formalizations as we obtain them.

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• cdyforever/how-to-live-betterHTML · 13,911 Stars

  在线阅读

  Stars 统计更新于 2026/11/1 09:56:01

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  作者描述

  《高性价比人生指南》全书 528 条的在线单页阅读版：手机可读、可搜索、零依赖、支持离线

  编报时的 AI 中文解读

  将开源书《高性价比人生指南》的全部内容渲染为单文件网页，供手机和电脑在线阅读与搜索，支持离线使用。

  编报时的 README 依据

  # 高性价比人生指南 · 在线阅读页 一个单文件 HTML 阅读页，把开源书《高性价比人生指南》的全部 32 节、528 条建议 渲染成可搜索的页面。手机上打开就能看，不用装任何东西。 **在线阅读：** https://cdyforever.github.io/how-to-live-better/ ## 这是什么 原书由 [eternity4719/HowToLiveBetter](https://github.com/eternity4719/HowToLiveBetter) 维护（Unlicense，公有领域），按「性价比」排序，每条写清花掉什么、换回什么、证据多硬， 只引期刊论文和官方文件。 本仓库不是原书的 fork，也不改动原书内容。它只做一件事：把原书正文渲染成一个 **自包含的单文件网页**，方便在手机和别人的电脑上直接打开。 ## 页面特性 - **零外部资源**：没有 CDN、没有字体外链、不 fetch 任何数据，断网也能读 - 逐条卡片：建议标题、证据等级（A/B/C）、性价比档、成本标签 - **「说人话」高亮块**——原书里这一栏专门把统计量翻成日常说法，页面上做得最显眼 - 全站关键词搜索（结果高亮）、只看 A 级、只看说人话 - 左侧目录带性价比色点，滚动联动 - 手机端：搜索框独占一行、顶栏向下滚动后自动收成一行、回到顶部按钮

  - 明暗主题切换 - 支持直接打印 ## 本地使用 不用构建，双击 `index.html` 即可。 ## 重新生成 ```bash # 需要先有一份上游仓库的本地克隆 git clone --depth 1 https://github.com/eternity4719/HowToLiveBetter.git /tmp/upstream # 全部 32 节 python build.py all -o index.html --repo /tmp/upstream # 只做某几节 python build.py 1 2 16 --repo /tmp/upstream ``` 源目录也可以用环境变量 `HLTB_REPO` 指定。 统计口径（条目数、A/B/C 分级、性价比三档）与上游的 `tools/sync-stats.ps1` 和 `index.html` 保持一致，生成结果可与上游徽章逐项对照。 ## 自动更新 `.github/workflows/rebuild.yml` 每天 06:00（北京时间）拉取上游重新生成， 内容有变化才提交。也可以去 Actions 页面手动触发。 ## 授权 原书内容为 Unlicense（公有领域）。本仓库的构建脚本同样不作任何权利保留。

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• Ebony-Vinyl/dsh-our-free-modelJavaScript · 54,406 Stars

  模型接口服务、用量统计、模型接口转发

  Stars 统计更新于 2026/11/1 09:40:55

  查看原始资料

  作者描述

  在 dsh 里装上这个插件即可，无需登录、注册或填 API Key，就能使用包括 DeepSeek V4.1 Flash、Kimi K3 在内的前沿模型——完全免费，不限量。 All you do is install this plugin in dsh: no login, no sign-up, no API key — the frontier models are just there, DeepSeek V4.1 Flash and Kimi K3 among them. Completely free, with no usage cap.

  编报时的 AI 中文解读

  为 DeepSeek Harness（dsh）提供免费模型接入的插件，安装后无需登录或 API Key 即可使用 DeepSeek、Kimi 等前沿模型，并附带用量看板、本地转发、聚合渠道与省 Token 等功能。

  编报时的 README 依据

  - **公告中心**——仓库维护者推送的公告流：未读计数、紧急徽章、单条/全部标记已读、检查新公告按钮、系统通知开关。公告正文按白名单渲染 HTML。 - **用量看板**——总览计数、17 周 Token 热力图、总量曲线（Token / 请求数切换，总计与单模型切换）、速度迷你图、按模型汇总表。 - **本地转发**——开关、监听地址与端口、复制 base URL、显示 / 复制 / 轮换 API Key，并提供可直接执行的 curl 示例。 - **插件设置**——总开关、是否展示地区受限模型、探测间隔、默认输出上限，以及当前探测到的出口 IP 与国家。 - **插件升级**——当前/最新版本、检查更新、一键升级（含进度与失败原因）、最近一次升级历史、热重载按钮与文件监视开关。 - **首次启动公告**——分 5 页（前言 / 模型清单 / 使用步骤 / 功能介绍 / 公告与升级），确认一次后不再弹出，除非文案版本号被提升。 ## 独立本地服务（开发中） 仓库现在提供两个入口：下文安装的是 **DSH 插件**；`packages/standalone` 是 **无需安装 DSH 的独立本地服务**。从完整源码仓库运行： ```powershell npm run start:standalone ```

  独立服务默认使用 `~/.our-free-model` 和端口 `18900`，拥有自己的 API Key， 不读取插件数据。支持匿名/Kilo、EAC 和十个账号渠道，提供 Chat Completions、Responses API，以及独立网页管理（模型、统计、渠道、EAC、设置、API Key）。 启动后打开终端打印的一次性管理链接即可使用；账号在独立页面登录，也可手动导入插件账号备份。 启动、参数与验证见 [独立服务说明](packages/standalone/README.md)。 独立服务的安装制品与 Release 尚未发布。 ## 安装 > **⚠️ 不要通过 npm 安装本插件。** > > npm 上的 `dsh-our-free-model` 包**不是本仓库发布的**。它由第三方打包，内容与本仓库 > 不一致：`index.js`、`client.js` 被改动，并额外包含本仓库从未有过的 > `src/channel-visibility.js`。装到它得不到本项目审核过的构建，也拿不到本仓库的签名 > 清单校验与应用内升级。 > > 请只按本文档下方的方式安装：使用本仓库的 Release 发布包，或本地源码目录。 > 其它渠道出现的同名包一律以本仓库为准。 **命令行（纯 dsh web）** ```

  <div align="center"> <img src="icon.svg" alt="Our Free Model — DeepSeek Harness 免费模型插件" width="120"> # dsh-our-free-model **简体中文** | [English](README_EN.md) <img alt="许可证" src="https://img.shields.io/badge/license-MIT-263146?style=flat-square"> <img alt="零依赖" src="https://img.shields.io/badge/dependencies-zero-4b6fff?style=flat-square"> <img alt="无构建步骤" src="https://img.shields.io/badge/build%20step-none-7da1de?style=flat-square"> <img alt="适配内核" src="https://img.shields.io/badge/dsh-0.1.5--0.1.7--rc.2-2f6f4f?style=flat-square">

  - **OpenAI 兼容转发端口**——本机其它工具通过 base URL 与 Key 即可调用这些模型。Chat 历史中 assistant 的字符串 `reasoning_content` 会随工具后续请求保留，包括显式空字符串；缺失字段不会被补造。 - **EAC 渠道（桌面端专属）**——在 DeepSeek Harness 桌面端与 DSHEAC AIO 桌面端中自动解锁一条协付通道，模型以 EAC 前缀显示（如 EAC DeepSeek V4.1 Flash）；凭据加密密封，由宿主指纹闸门把守；该渠道在服务器侧校验 GitHub 授权（登录并 star 本仓库）后才放行对话；在命令行及其它宿主中该通道完全不存在。详见「EAC 渠道」。

  DSH 插件本体无需构建、解压即用；**桌面安装包**（Our Free Model 桌面壳）官方目前只发布 Windows 版。macOS 版为社区构建：源码改动见 [PR #421](https://github.com/Ebony-Vinyl/dsh-our-free-model/pull/421)，可逐行审计；预打好的 Apple Silicon（arm64）包以社区 Release 的版本和校验值为准，也可以自己从源码构建（macOS 上执行 `npm --prefix packages/desktop run build`，完整流水线见 `.github/workflows/build-macos.yml`）。 下载后建议先核对校验和（SHA256 见 PR / Release）： ```bash shasum -a 256 ~/Downloads/Our.Free.Model_<version>_aarch64.dmg ``` **安装后提示「已损坏」或打不开？** 社区构建没有 Apple Developer 账号签名与公证，Gatekeeper 会拦截首次启动——这不是文件真的损坏，以下几种方式任选其一： 1. **右键打开**：在访达中按住 Control 点按应用图标，选择「打开」，在弹窗中再次点按「打开」。 2. **清除隔离属性**（终端）：

  查看 README 缓存打开 GitHub
• yetone/magpieGo · 26,986 Stars

  模型切换、模型接口转发、用量统计

  Stars 统计更新于 2026/11/1 09:56:09

  查看原始资料

  作者描述

  Every agent's model. One place. Codex on DeepSeek, Claude Code on Kimi, from the menu bar.

  编报时的 AI 中文解读

  magpie 是一个本地网关应用，让用户从菜单栏为多个 AI 编码代理（如 Claude Code、Codex）切换模型、提供商和账户，并支持配额耗尽时自动切换。适用于使用多个代理、多个提供商或多个账户的用户。

  编报时的 README 依据

  - **Keep your secrets off the vendor's servers**: once you turn masking on in **Settings → Privacy** (it's off by default), keys, passwords and emails in a prompt are masked on your computer before the request leaves it, and put back in the reply. It's for you if you use more than one agent, more than one provider, or more than one account. If you use one agent on its vendor's own plan and that's enough, you don't need it. Runs on macOS, Windows and Linux (menu bar app, window, TUI, web UI and CLI), in Docker, and on Termux. ## Quick start

  **3 · Pick a model** for each agent on the **Agents** page. Start a new session and it's on the new model. Or do it all from the terminal: ```sh magpie provider add deepseek sk-… # a preset needs only the key magpie claude deepseek/deepseek-v4-pro # Claude Code on DeepSeek magpie codex moonshot/kimi-k2.5 # Codex on Kimi magpie group add "Opus anywhere" models=claude/claude-opus-5-5,copilot/claude-opus-5.5 routing=smart magpie claude group/opus-anywhere # fails over between subscriptions

  switch; the [reference](docs/reference.md#counting-users) has the rules. ## Community Questions, ideas, or a model that won't show up? Tell us on **[Discord](https://discord.gg/vGSnD3ZKQF)**. That is where feedback goes. **This repository doesn't take pull requests.** Only maintainers can open them. If you'd like a fix or a feature, describe it on Discord and we'll build it. If magpie saved you from editing one more config file, **a ⭐ helps others find it.** <a href="https://star-history.com/#yetone/magpie&Date"> <picture>

  查看 README 缓存打开 GitHub
• deepseek-ai/DeepInferPython · 24,669 Stars

  模型本地部署

  Stars 统计更新于 2026/11/1 10:25:49

  查看原始资料

  作者描述

  DeepInfer: High-performance, large-scale inference framework for DeepSeek models

  编报时的 AI 中文解读

  DeepInfer 是 DeepSeek 官方开源的高性能大规模推理框架，用于在 NVIDIA 或华为昇腾硬件上离线部署和运行 DeepSeek-V4.1-Flash 模型，提供优化的内核、并行策略和结构化输出等核心服务能力。

  编报时的 README 依据

  - Linux - GCC >= 13.0 - Python 3.12 - CUDA 13 (NVIDIA only) - CANN 9.2 (Ascend only) ### Build from source Before building DeepInfer, please create and activate an empty Python 3.12 environment. ``` bash # Use `ascend` instead for the Ascend platform # Keep it exported in the environment where you run DeepInfer export DEEPINFER_ACCELERATOR=nvidia ./build.sh ``` ### Offline inference The default checkpoint, [`deepseek-ai/DeepSeek-V4.1-Flash-1017`](https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash-1017), is

  downloaded into the Hugging Face cache on the first run; set `DEEPINFER_HF_MODEL_DIR=/path/to/DeepSeek-V4.1-Flash-1017` to run from a local copy instead. ``` bash python examples/offline_inference.py ``` See [examples](examples/README.md) for details. ## Performance benchmarks | Prefill | Decode | | :---: | :---: | | [](doc/images/prefill_pareto.png) | [](doc/images/decode_pareto.png) |

  - **Structured outputs:** constrain generation to a regex, JSON schema, or EBNF grammar. Pass `so_args={"schema_type": ..., "schema": ...}` to `SamplingParams`; see [examples](examples/_structured_output.py). </details> Supported hardware: - NVIDIA SM100 GPUs - Huawei Ascend 950 NPUs Required for a complete inference service (not included in this release): - A KV cache system - VE/Prefill/Decode disaggregation (most required engine functionality is already implemented) - Load balancing across data-parallel replicas for both prefill and decode ## Getting started ### Prerequisites

  查看 README 缓存打开 GitHub
• storytold/pdfcraftRust · 18,946 Stars

  PDF处理、PDF合并拆分、PDF加密

  Stars 统计更新于 2026/11/1 10:21:05

  查看原始资料

  作者描述

  PdfCraft: An open-source PDF reader and editor written by scratch in pure Rust

  编报时的 AI 中文解读

  PdfCraft 是一款用纯 Rust 编写的开源 PDF 阅读器和编辑器，支持阅读、组织、合并、拆分和保护 PDF 文件，适用于需要处理 PDF 文档的个人用户和专业人士。

  编报时的 README 依据

  - **Engine first.** Parsing, rendering and editing live in reusable library crates. The interface is one swappable layer on top. - **Scriptable.** The `pdfcraft-cli` tool (see [Built for agents, too](#built-for-agents-too)) covers inspecting, rendering, extracting text, editing, combining, extracting pages and splitting. Robustness sweeps run on the same engine as the app. ```sh pdfcraft-cli info form.pdf # structure as JSON pdfcraft-cli text paper.pdf --page 3 # reading-order text

  pdfcraft-cli edit in.pdf --rotate 1,2:90 --delete 5 --title "Q3" --out out.pdf ``` --- ## Built for agents, too Every engine feature is reachable without the GUI, through one table of JSON-Schema-described tools: open, inspect, render pages to PNG, extract and find text, rotate, delete, move and insert pages, edit bookmarks and page labels, add, reply to, restyle and delete comments (highlight a phrase just by naming it), list and fill in form fields, protect with passwords, set metadata, undo and redo, save, combine, extract and split. Three front doors share it:

  PdfCraft is a clean-room implementation. Its behaviour comes from the ISO 32000 specification and black-box observation, never from anyone else's code. Every icon, font and image is openly licensed and listed in [ATTRIBUTION.md](ATTRIBUTION.md). ## Get started Building needs Rust 1.95 or later. ```sh git clone https://github.com/storytold/pdfcraft cd pdfcraft cargo xtask models # fetch the OCR models Scan & OCR needs (release builds include them) cargo run --release -p pdfcraft -- some.pdf # desktop app

  Right-click a PDF tab to close it, reopen the last closed file-backed tab, or reveal its file. Closing still asks about unsaved changes. Reopening reads the saved file from disk; it does not restore discarded edits. Reveal selects the file in Explorer or Finder. On Linux and FreeBSD it requests `org.freedesktop.FileManager1.ShowItems`, falling back to opening the containing directory with `xdg-open` when that service is unavailable. Reopen and Reveal are unavailable on the web; Reveal is also unavailable for pathless documents.

  查看 README 缓存打开 GitHub
• storytold/filmcraftRust · 17,090 Stars

  视频剪辑、视频调色、音频编辑

  Stars 统计更新于 2026/11/1 10:21:14

  查看原始资料

  作者描述

  FilmCraft: An open-source, nonlinear video editor written by scratch in pure Rust

  编报时的 AI 中文解读

  FilmCraft 是一款用纯 Rust 编写的开源专业非线性视频编辑器，支持视频剪辑、调色、音频处理和导出，可在 macOS、Windows、Linux 及浏览器中运行。

  编报时的 README 依据

  - **Swappable UI.** The interface is one crate (`ui-egui`) over the engine, so a different front end can replace it without touching editing logic. <br> ## Get started ```sh cargo run --release -p filmcraft # the desktop app, with a demo project cargo run --release -p filmcraft -- --control 9876 # plus the JSON-lines control server cargo run --release -p filmcraft-cli -- commands # list every engine command cargo run --release -p filmcraft-cli -- mcp # MCP server (headless) ```

  {"method": "ui.screenshot", "params": {"path": "frame.png"}} ``` The trailer and the grades in these screenshots were built exactly this way, by an agent driving the running app. <br> ## Everywhere - **Native** on macOS, Windows and Linux, with a native macOS menu bar. - **The web:** the same engine and UI run in the browser via WebAssembly (`apps/filmcraft-web`, see [docs/web.md](docs/web.md)); every release ships it as `filmcraft-web-<version>.zip`.

  FilmCraft is young and moving fast. Editing, trimming, multicam, colour, keyframes, effects, titles, captions, mixing, codecs and export work today. FilmCraft is in **alpha**. We track two numbers ([docs/target-app-parity.md](docs/target-app-parity.md), re-measured 2026-10-10): - **Feature breadth: ~86%.** Professional NLE menu items, effects, transitions, panels and formats that exist in FilmCraft (menus 92% and effects 100% measured). - **Ready for real work: ~56%.** Our honest estimate of how close FilmCraft is to handling full production work on real projects. The biggest gaps today:

  - **Speed on big footage.** Hardware decoding works on macOS and Windows, and for H.264 and HEVC on Linux (VA-API, or NVDEC with NVIDIA's driver; VP9 and AV1 decode in software there). Blend modes and the most common effects run on the GPU, but color grading, keys and export rendering still run on the CPU; H.264 encoding can use the hardware encoder on macOS and on

  查看 README 缓存打开 GitHub
• Droid-Deck/DroidDeckKotlin · 16,870 Stars

  游戏运行、商店集成

  Stars 统计更新于 2026/11/1 09:40:55

  查看原始资料

  作者描述

  DroidDeck brings the SteamOS experience to Android

  编报时的 AI 中文解读

  DroidDeck 是一个 Android 应用，旨在将 SteamOS 体验带到安卓设备上，让用户通过 Valve 的 Steam 客户端和 ARM64 Proton 在 Adreno 掌机上运行 Windows 游戏。 该应用支持安装 Linux 桌面环境和模拟器，并集成多个游戏商店（如 GOG、Epic Games、Amazon Games），方便用户管理和启动游戏。

  编报时的 README 依据

  > Note: DroidDeck does not have a stand-alone website. Do not click on any download links from websites claiming to be the DroidDeck team. ## Requirements and install Use Android 9 or newer on a supported Adreno device (730 or newer, or 8xx). Adreno 6xx is experimental: DirectX 11 uses DXVK 2 and may run, and DirectX 12 games can still crash. Mali, Xclipse, PowerVR, and Adreno 710 are unsupported. No root is required. Allow about 3 GB for the runtime and 1.1 GB more for the desktop and emulators. Install the APK from [Releases](https://github.com/Droid-Deck/DroidDeck/releases), install the

  Linux runtime, then press **Play** and sign in. Steam downloads on first launch. Install **Desktop & apps** to use the desktop and emulators. The **Store** installs Linux apps and games from Flathub (ARM64 builds) with Flatpak; with additional options to install Appimages and set up scripts. **Stores** (Setup › Stores › "Show Stores in the rail") signs in to GOG, Epic Games and Amazon Games and downloads games into the Games storage. Epic keeps its direct API install path. Opening Epic Stores prepares Epic’s official Linux launcher preview. When installed, Epic games launched from DroidDeck

  verification manifest. Run the helper and preload regression suite with `bash tools/test_local.sh`. On macOS it runs in Linux through Docker, matching the helpers' runtime and CI instead of compiling Linux preloads against macOS headers. ## Limits Compatibility and performance vary by device; hardware validation is limited. Desktop compositing uses software rendering. Firefox sandboxing is reduced under proot. Logs are kept app-private (`files/logs/`, the last 30 sessions); **Share logs** packs the newest session, with the stores and tool logs, into one scrubbed zip.

  查看 README 缓存打开 GitHub
• storytold/lightcraftRust · 15,190 Stars

  照片管理、RAW处理、照片调色

  Stars 统计更新于 2026/11/1 09:45:51

  查看原始资料

  作者描述

  LightCraft: An open-source non-destructive photo editor written by scratch in pure Rust

  编报时的 AI 中文解读

  LightCraft 是一款开源的、非破坏性照片编辑器和照片库管理工具，使用纯 Rust 编写，支持 RAW 格式处理，可在桌面和浏览器中使用，并可通过 MCP 协议由 AI 代理驱动。

  编报时的 README 依据

  <a href="README.md">English</a> · <a href="README.zh-hans.md">简体中文</a> · <a href="README.zh-hant.md">繁體中文</a> </p> <p align="center"> <b>Photo library and raw development; an open-source, non-destructive photo library and raw developer, built in pure Rust.</b><br> Native on macOS, Windows and Linux. In the browser via WebAssembly. Drivable end to end by AI agents over MCP. </p> <p align="center"> <img alt="Pure Rust" src="https://img.shields.io/badge/pure-Rust-f2a516?style=flat-square&logo=rust&logoColor=white">

  </table> <br> ## Built for agents Every menu item, slider, brush stroke, crop handle and keystroke in LightCraft is a **command** with a stable id and JSON parameters. The UI, the keyboard, the CLI, a JSON-lines control channel and an **MCP server** all dispatch through the same entry point. An agent can cull a shoot, develop it, mask a sky and export it, and *see* the result. ```sh lightcraft --control 7980 ~/Pictures/trip ``` ```jsonc {"method": "engine.execute", "params": {"command": "photo.flag", "params": {"flag": "pick"}}}

  installed model; see [model setup and terms](docs/ai-masks.md). Subject, Sky and Background selections still use classical heuristics. Existing model-generated masks render and export without the model installed. <p align="center"> <img src="docs/images/masking.jpg" alt="Masking panel with a linear Sky mask and a radial Sun glow mask; the radial gradient is drawn as a red overlay around the sun on a lake scene" width="100%"> <br>

  - **compressed Olympus raws and unsupported CR3 variants:** these use embedded JPEG previews when present. Fujifilm lossless/lossy compressed RAF now decodes sensor data; [verification and existing-library reload instructions](docs/raf-compression.md); - **AI quality and model setup:** Subject and Sky selection are classical heuristics; Object/Describe use an optional SAM 3 model. AI Denoise supports Bayer RAW with separately installed weights, while X-Trans and

  human-readable operations you can diff, back up or replay. <br> ## Feature status LightCraft is young and moving fast: **alpha**. **Where we honestly stand** (details in the [roadmap](ROADMAP.md) and [docs/target-app-parity.md](docs/target-app-parity.md)): - **By feature count we're at ~82%** (core features 98%), tracked row by row in [docs/parity-checklist.md](docs/parity-checklist.md). - **As a day-to-day tool we're nearer 61% for the whole product, ~51% for a typical working photographer and ~65% for casual use.** It's great for JPEG/DNG and most Sony / Panasonic /

  Fujifilm / Nikon / older-Canon raws on one machine; see [docs/raw-parity.md](docs/raw-parity.md) for your camera. - **The biggest gaps:** - **camera colour calibration:** Sony, Nikon, Panasonic, Fujifilm and Canon CR3 raws have guarded estimates from their camera JPEGs, with built-in ILCA-99M2, ILCE-7CR, ILCE-7M4, ILCE-7RM5, X-H2S, X-T4, Nikon Z 6II, Z 8 and D5300 profiles; measured calibration is missing, and other raws or rejected fits retain a neutral matrix;

  linear-RGB denoise and Super Resolution remain missing; see [AI masks](docs/ai-masks.md) and [AI Denoise](docs/denoise.md); - **network libraries:** a preview reads the raw's header — or, for a CR3 or a TIFF raw whose preview tag sits past it, exactly the ranges the sparse planner names — and its embedded JPEG only (56.5 MB → 5.9 MB, 10 s → 1 s on the test share), but the *developed* picture still needs the sensor data over the wire; see [docs/raw-preview-reads.md](docs/raw-preview-reads.md);

  查看 README 缓存打开 GitHub
• shihabal3amri/DiPlayKotlin · 12,966 Stars

  CarPlay接入

  Stars 统计更新于 2026/11/1 10:20:53

  查看原始资料

  作者描述

  Independent CarPlay receiver for compatible Android head units. Wired and wireless public preview.

  编报时的 AI 中文解读

  DiPlay 是一个独立的 CarPlay 接收器应用，专为兼容的比亚迪 Android 车载主机设计，支持有线和无线连接，并提供类似 DiAuto 的界面。适用于希望在比亚迪汽车上使用 CarPlay 功能的用户。

  编报时的 README 依据

  # DiPlay [English](README.md) · [简体中文](README.zh-CN.md) · [繁體中文](README.zh-TW.md) **CarPlay for compatible BYD Android head units.** Wired and wireless, with the familiar DiAuto interface. Independent app: `com.shihab.diplay`. > **BYD support scope:** These projects focus on BYD cars. They may work on other brands, but other brands are unsupported and there are no plans to add support or fix brand-specific incompatibilities.

  Install on the **car**, not the iPhone. No jailbreak, dongle, Mac, account or authentication server is required for use. Core CarPlay does not require ADB; optional dashboard, battery, wheel-speed and parked-video features do. Your head unit must permit APK installation. The APK supports Android 7.0+ (API 24); on Android 7.0–8.1, wired CarPlay is confirmed on one car and wireless is not yet confirmed on a vehicle. Wireless supports Wi-Fi Direct, the car’s existing hotspot or Existing Wi-Fi / Same LAN. Android 7.0–9 Wi-Fi Direct uses a firmware-dependent legacy path with generated group

  - Local diagnostic export. Reports are sent only if you choose to share them. - Separate installation alongside DiAuto. Run one projection app at a time. This is **not an Apple-certified product**. The APK bundles an experimental accessory identity recovered from public Carlinkit firmware, not a newly provisioned MFi identity for DiPlay. A bundled private key is extractable. Acceptance after future iOS updates, reliability across head units and suitability of that identity for general distribution are unresolved. This release invites community testing; it is not a guarantee of universal

  查看 README 缓存打开 GitHub
• yihui-dev/awesome-opus5-5-videos未标注语言 · 12,912 Stars

  提示词参考、视频制作

  Stars 统计更新于 2026/11/1 10:21:17

  查看原始资料

  作者描述

  A growing collection of viral videos made with Claude Opus 5.5 and the prompts behind them. Watch each original next to a live remake on Skillry. Updated regularly.

  编报时的 AI 中文解读

  这是一个收集用Claude Opus 5.5制作的病毒式传播视频及其提示词的资源合集，每个视频都附有创作者分享的提示词或原始帖子链接，适合想用AI生成动画的创作者参考。

  编报时的 README 依据

  Every video here was made by asking Claude Opus 5.5 to write the animation as code (HTML, Canvas, SVG, Three.js and friends). Pick one, copy its prompt, and try it with your own agent. **[▶ Watch all 418 side by side with live remakes on Skillry](https://skillry.dev/ai-videos/opus-5-5?utm_source=github&utm_medium=readme&utm_campaign=awesome-opus5-5-videos)**

  <a href="https://skillry.dev/ai-videos/opus-5-5?utm_source=github&utm_medium=readme&utm_campaign=awesome-opus5-5-videos"><img src="https://media.skillry.dev/opus-5-5/_readme/site-compare.592de731e6.webp" alt="The Opus 5.5 videos page on Skillry, showing each original next to its live remake" width="100%"></a> - 703 prompts in [`prompts/`](prompts/) and [`data/videos.json`](data/videos.json), 418 of them with a live remake on Skillry - 100 remade videos highlighted below, one per distinct prompt - Every entry links to the creator's original post

  查看 README 缓存打开 GitHub
• storytold/vectorcraftRust · 11,133 Stars

  矢量插画、矢量编辑、AI辅助绘图

  Stars 统计更新于 2026/11/1 10:21:14

  查看原始资料

  作者描述

  VectorCraft: An open-source, vector art tool written by scratch in pure Rust

  编报时的 AI 中文解读

  VectorCraft 是一款开源、现代的矢量插画应用，使用纯 Rust 编写，支持 macOS、Windows、Linux、FreeBSD 及浏览器（WebAssembly）。它提供熟悉的界面和工具，如钢笔、路径查找器、渐变网格、3D 旋转等，并支持 SVG、PDF、AI 等格式的导入导出。

  编报时的 README 依据

  control channel and an **MCP server**, so Claude and other agents can draw, edit and export the way a person does. - **Everywhere.** One codebase for the desktop apps and the same UI in the browser. ## Quick start For posters and sewing patterns, see [Print a large poster across multiple pages](docs/print-tiling.md). ```sh git clone https://github.com/storytold/vectorcraft cd vectorcraft cargo run --release -p vectorcraft # desktop app cargo run --release -p vectorcraft -- examples/dusk-poster.vectorcraft

  cargo run --release -p vectorcraft -- --control 7979 # + JSON control channel cargo run --release -p vectorcraft-cli -- mcp # MCP server (stdio) cargo run --release -p vectorcraft-cli -- run --in examples/ribbons.vectorcraft --export out.pdf # headless batch cargo run --release -p vectorcraft-cli -- bench examples/neon-drive.vectorcraft # render timing cargo xtask bundle # dist/VectorCraft.app (macOS) cd apps/vectorcraft-web && trunk build --release # web build → dist/web

  | Debian/Ubuntu | `vectorcraft-<ver>-linux-x86_64.deb` | `vectorcraft-<ver>-linux-aarch64.deb` | | | Fedora/RHEL/openSUSE | `vectorcraft-<ver>-linux-x86_64.rpm` | `vectorcraft-<ver>-linux-aarch64.rpm` | | | Tarball | `vectorcraft-<ver>-linux-x86_64.tar.gz` | `vectorcraft-<ver>-linux-aarch64.tar.gz` | Unpack anywhere | ### FreeBSD | Build | File | |---|---| | x86_64 | `vectorcraft-<ver>-freebsd-x86_64.tar.gz` | ### Web (WebAssembly) | Build | File | Notes | |---|---|---| | Static site | `vectorcraft-web-<ver>.zip` | Runs in a modern browser; host it on any static server |

  **Where we are (2026-10-10): alpha.** About 88% of core menu items, tools, effects and formats exist (92.5% of menu items do something), feature depth is ~75%, and we estimate ~65% ready for real work for a mainstream illustrator (~62% across all tracked features): everyday vector illustration is close to usable: drawing and path tools, Pathfinder and Shape Builder, paint, gradients, appearance and transparency, type with styles, threading and Hebrew/Arabic bidirectional layout, and

  - reliable exchange of .ai files (layer structure in real files; proprietary editing data isn't written); - an interaction-fidelity pass covering every tool's modifiers and small behaviours; - 3D and Materials beyond the initial live Revolve (Extrude & Bevel, Inflate, Rotate, materials); - filter thumbnails and a preview area inside the Effect Gallery (the gallery itself and all 57 Photoshop-style raster filters, approximated, are in); - CJK composition for vertical type (vertical type itself has initial support, with a Japanese interface);

  - scripting, and the rest of Variables (image and graph kinds, dataset import); - generative AI features. **Where we're going:** next is the interaction-fidelity pass, `.ai` files from real users and start-up stability, alongside the raster-effects package; then type, recent additions and 3D. The ranked list is in [`docs/gaps.md`](docs/gaps.md). **Workspace:** `crates/{geom, color, doc, pathops, text, effects, three-d, trace, brush, render, svg, pdf, eps, cad, metafile, format, tools, engine, ui-egui, mcp, testkit}`

  查看 README 缓存打开 GitHub
• jaredpalmer/kevPython · 9,737 Stars

  文本分类、文本评分、模型微调

  Stars 统计更新于 2026/11/1 09:45:58

  查看原始资料

  作者描述

  Jev-like family of decision models built on top of Qwen3.5/3.8 you can train and run on your own

  编报时的 AI 中文解读

  Kev 是一系列小型决策模型，基于 Qwen3.5/3.8 构建，可自行训练和运行，用于对文本进行是非、多选和评分等结构化判断。

  编报时的 README 依据

  "state": "Shoes arrived two weeks late and in the wrong size. Also I see two charges on my card.", "model": "kev-latest", "questions": { "department": {"type": "choice", "instructions": "Which team should handle this?", "criteria": {"returns": "Exchanges, refunds, wrong or damaged items", "shipping": "Delivery status, delays, lost packages", "billing": "Charges, invoices, payment problems"}}, "escalate": {"type": "noul", "instructions": "Does this need urgent human attention?"},

  "frustration": {"type": "score", "instructions": "How frustrated is the customer?", "criteria": ["Calm", "Frustrated", "Very angry"]} }}' ``` Example response from Kev-4B, running in bf16 on an Apple M5: ```json { "model": "kev-latest", "answers": { "department": { "type": "choice", "choice": "returns", "confidence": 0.21, "probabilities": { "returns": 0.47, "shipping": 0.28, "billing": 0.25 } }, "escalate": { "type": "noul", "noul": 0.93 }, "frustration": { "type": "score", "score": 1.44, "confidence": 0.34,

  > [!WARNING] > PyPI name collision: `pip install kev` installs a **different package** — [K.E.V. ORM](https://pypi.org/project/kev/) (Brian Jinwright, 2016-2021). This project is **not** published to PyPI. Install from source as below. You'll need Python 3.12 or 3.13 and [uv](https://docs.astral.sh/uv/). The repo's `.python-version` makes `uv sync` use 3.13; torch has no wheels for 3.14 yet. ```bash git clone https://github.com/jaredpalmer/kev.git && cd kev uv sync --extra serve uv run --extra serve python -m kev.serve --run jaredpalmer/kev-4b --port 8009 ```

  If you already call Jev, point your client at Kev and keep the rest of your code. The TypeSafe SDK is included in `uv sync --extra serve`: ```python from typesafe_sdk import Choice, Noul, Score, TypeSafeClient client = TypeSafeClient( api_key="local", base_url="http://127.0.0.1:8009", model="kev-latest", ) response = client.system_one( state="I was charged twice. Please fix this ASAP.", questions={ "billing": Noul(instructions="Is this ticket about billing?"), "tone": Choice( instructions="What is the customer's tone?",

  This starts Kev-4B on your machine: CUDA or ROCm if you have a GPU, MLX on Apple Silicon. The first run downloads the adapter and the base model. `--run` also accepts a local checkpoint directory or a Hub revision like `jaredpalmer/kev-4b@qwen3`. Use `--device cpu` to skip accelerator discovery, or `--device cuda` / `--device mps` to require that accelerator. The default, `--device auto`, tests an allocation and matrix multiplication in a separate process before loading weights.

  **Length.** Kev-0.8B, 4B and 9B trained mostly on states of up to 384 tokens, with longer ones in their document and skill fine-tunes (up to 7,552 tokens), Kev-27B on states of up to 32,768. The server accepts states of up to 65,536 tokens, and 8,192 more for each question, and refuses a longer one with a 422 instead of cutting it. How far past its training length each model stays accurate is the "Validated context" column in [Models](#models). For Kev-0.8B, 4B and 9B that is 8,192 tokens: at 16k the measurement on real contracts can no longer rule out a drop of more than 3 points, and at 32k

  查看 README 缓存打开 GitHub
• rehan-remade/universal-modderPython · 9,291 Stars

  游戏模组制作、逆向工程、资源生成

  Stars 统计更新于 2026/11/1 10:21:14

  查看原始资料

  作者描述

  Point Claude at any game. Skills, tools and the fal MCP that let Claude Code mod almost any PC game you own: recon, reverse engineering, fal-generated art/3D/audio, in-game testing, showcase videos.

  编报时的 AI 中文解读

  为AI编码代理提供技能、工具和知识库，使其能够为PC游戏制作模组，包括逆向工程、资源生成、游戏内测试和视频展示。

  编报时的 README 依据

  Pick your agent. Each gets the same skills (Agent Skills format), the fal MCP server, and the `um` CLI. | Agent | Install | |---|---| | **Claude Code** | `/plugin marketplace add rehan-remade/universal-modder`<br>`/plugin install universal-modder@universal-modder` | | **Codex** | `codex plugin marketplace add rehan-remade/universal-modder`<br>`codex plugin add universal-modder@universal-modder` | | **Gemini CLI** | `gemini extensions install https://github.com/rehan-remade/universal-modder` |

  | **Skills only**<br>(any agent) | `npx skills add https://github.com/rehan-remade/universal-modder` | | **Anything else** | `git clone https://github.com/rehan-remade/universal-modder` and start your agent inside it | Inside a clone, each agent finds the skills where it looks for them: `.agents/skills` (Codex, Gemini CLI, Copilot, Cursor, OpenCode) and `.claude/skills` (Claude Code) are copies of `skills/`. Instructions are in `AGENTS.md`, which `CLAUDE.md` and `GEMINI.md` point to. MCP config is in `.mcp.json`, `.codex/config.toml`,

  Claude Code (`.claude/settings.json`); in a clone with another agent, `export PATH="$PWD/bin:$PATH"`. Other agents' plugin installs (Codex, Cursor, Gemini CLI, OpenCode) don't, so install it once: ```bash uv tool install git+https://github.com/rehan-remade/universal-modder # or: pipx install git+... ``` **For assets,** get a [fal API key](https://fal.ai/dashboard/keys). It powers both the fal MCP server and `um fal`. Rather than exporting it from a shell profile or a `.env`, store it once with `um fal key set`: on

  and `um comfy` makes images on a local ComfyUI server. `um sprixen` (2D sprites, animation sheets, tiles) uses Sprixen, a separate paid service with its own [API key](https://sprixen.com/settings/api) (`um sprixen key set`). `um voidless` (2D sprites, 8-way turns, animation sets) uses Voidless, also a separate paid service with its own [API key](https://voidless.dev/api-docs) (`um voidless key set`). ```bash um fal key set # hidden prompt export FAL_KEY="$(secret-tool lookup service fal.ai key api)" # Linux: before starting the agent ```

  You also need Git, Python 3.10+ and ffmpeg. `uv` is recommended. Blender is needed for 3D → sprite renders. Windows games are driven natively or from WSL. ## Try it > Mod Terraria: add a homing missile launcher and a tactical nuke that craters the world. Make the sprites with fal. > Make a new civilization for Age of Empires II with a unique unit rendered from 3D. > Put real Minecraft inside GTA V story mode. Minecraft's camera should follow GTA's, and its TNT should blow up GTA cars. > Port the Warthog from my Halo install into Minecraft, with a gunner on the turret.

  - Minecraft's colour + depth are depth-composited into GTA's frame. - Minecraft TNT, arrows and fireworks become GTA explosions and bullets, and Minecraft mobs fight the police. Each has a field note with every non-obvious lesson: [knowledge/INDEX.md](knowledge/INDEX.md). ## Rules it follows - **Any game you own: single-player, multiplayer, or servers you host.** It refuses to inject into online games with anti-cheat, write cheats against other players, or bypass anti-cheat, DRM or ownership checks.

  - **It never ships game files or decompiled code.** Mods ship as code, your own assets, patches or converters. - **It backs up before touching saves**, and kills processes by PID only. - **It asks before** driving your mouse and keyboard, installing loaders into game folders, or publishing, PRs included. Full reasoning: [`skills/mod-any-game/references/safety.md`](skills/mod-any-game/references/safety.md). ## Made a mod with it? Show it off in the [Discord](https://discord.com/invite/sEZWaf7vV), and put the badge on your mod's page: <p>

  查看 README 缓存打开 GitHub
• KKKKhazix/AIHOTTypeScript · 8,987 Stars

  热点追踪、日报生成、资讯聚合

  Stars 统计更新于 2026/11/1 10:25:51

  查看原始资料

  作者描述

  一个自己找热点、自己写日报的网站框架。把信源和精选标准换成你的，它就是你的行业热点站。

  编报时的 AI 中文解读

  AIHOT 是一个可定制的行业热点网站框架，能自动从信源采集资料，通过大模型筛选、评分、聚簇生成热点和日报，适合为特定行业构建热点站。

  编报时的 README 依据

  <img src="https://img.shields.io/badge/PostgreSQL-17-176b75?style=flat-square&logo=postgresql&logoColor=white" alt="PostgreSQL 17"> <img src="https://img.shields.io/badge/Docker-Compose-176b75?style=flat-square&logo=docker&logoColor=white" alt="Docker Compose"> <a href="https://aihot.news"><img src="https://img.shields.io/badge/%E7%BA%BF%E4%B8%8A%E5%8E%9F%E7%AB%99-aihot.news-202a30?style=flat-square" alt="线上原站 aihot.news"></a> </p> <p align="center"> <b>一个自己找热点、自己写日报的网站框架。</b><br> 把信源换成你的，把精选标准换成你的 KnowHow，它就是你的行业热点站。 </p> <p align="center">

  <b>简体中文</b> · <a href="README.en.md">English</a> </p> <p align="center"> <a href="#跑起来">跑起来</a> · <a href="docs/customize.md">改成你的行业</a> · <a href="#它是怎么工作的">它是怎么工作的</a> · <a href="#文档">文档</a> · <a href="https://github.com/KKKKhazix/AIHOT/discussions">社区交流</a> </p> <br> ## 这是什么 [AIHOT](https://aihot.news) 是我做的一个 AI 热点网站。它每天从一批信源里收资料，用大模型先筛一遍、再独立打两次分，挑出真正值得看的，写成中文标题和摘要；把不同来源说的同一件事聚成一个事件，按有多少人在说排出热点；每天早上出一份日报。 这个仓库是它的引擎和框架：网站、后台、精选流程、聚簇和热度算法，**所有提示词的原文和入选门槛**，都在这里。 ## 为什么开源 这半年，很多做法律、做 HR、做金融、做贵金属的朋友问我，能不能也给他们的行业做一个。 我做不了。我不懂你们的行业，不知道哪些信源有用，也不知道什么样的消息，对你们来说才叫热点。 但你们懂。

  <img src="docs/assets/shots-light.png" alt="首页的每日精选，关于页的信源河" width="100%"> </picture> <p align="center">_{截图来自用示范信源跑起来的本地站，站名是默认的 MyHOT。}</p> ## 跑起来 想创建自己的独立站点，可以先点 [Use this template](https://github.com/KKKKhazix/AIHOT/generate)，再克隆你生成的仓库。想持续合并上游更新或贡献代码，建议先 Fork。下面的命令适合直接试用。 需要 [Docker](https://docs.docker.com/get-started/get-docker/)、[Node.js 24](https://nodejs.org/en/download)（运行 `init-env` 生成配置要用），和一个 OpenAI 兼容的模型 API Key（DeepSeek、千问、智谱都可以）。

  `init-env` 默认按 DeepSeek 配置。用千问、智谱等别家，照 `.env.example` 里的例子改 `.env` 的 `LLM_BASE_URL`、`LLM_MODEL` 和 `LLM_EXTRA_JSON`；用推理模型（先想再答）时，还要设 `LLM_REASONING_TOKENS` 给推理留出输出额度。 ```bash git clone https://github.com/KKKKhazix/AIHOT.git myhot cd myhot node scripts/init-env.ts --llm-key <你的模型 API Key> docker compose up -d --build ``` 打开 <http://localhost:3000>。后台在 `/admin`，管理员密码在 `.env` 的 `ADMIN_PASSWORD` 里。一两分钟后开始有内容，第一次导入的资料大约半小时处理完。 机器上没有 Node、服务器在中国大陆、要配域名和 HTTPS，或者不用 Docker、直接在 Linux、macOS 上跑（Windows 用 WSL2），见 [部署](docs/deploy.md)。

  既然我没办法满足所有人，那就把火种交到大家自己手上。 ## 说在前面 - **我不是专业的开发者。** 我是设计师出身，半年前还看不太懂代码。这套代码是我和 AI 一起重写的，比以前干净了很多，但一定还有写得不好的地方。发现问题欢迎提 Issue，我不一定能很快回复，先说声抱歉。 - **这是 AIHOT 的引擎。** 它和 AIHOT 线上跑的是同一份引擎代码，同步时直接从线上导出，不是精心打磨的通用框架。以后 AIHOT 的更新，我会尽量同步过来，但没法保证每一次都同步。模型榜、Codex 重置监控、主题页的大事记这些只对 AI 行业有意义的功能，以及 AIHOT 自己的运营工具，只留在 AIHOT 上。 - **里面没有 AIHOT 的信源名单和运营数据。** 仓库带了 18 个公开的海外 AI 资讯源做示范，够你跑起来看效果；真正的信源，要换成你自己行业的。 - **请不要用 AIHOT 的名字和 Logo。** 换上你自己的名字，它就是你的站。 ## 它是怎么工作的 <picture> <source media="(prefers-color-scheme: dark)" srcset="docs/assets/how-dark.png">

  查看 README 缓存打开 GitHub
• zai-org/ZCodeTypeScript · 8,404 Stars

  AI辅助编程

  Stars 统计更新于 2026/11/1 10:20:57

  查看原始资料

  作者描述

  Z.ai's coding agent harness. Powerful, intelligent, extensible.

  编报时的 AI 中文解读

  ZCode 是一个 AI 编程工作台，提供桌面应用、浏览器界面和终端 Agent，用于辅助编程任务。

  编报时的 README 依据

  # ZCode <div align="center"> <img src="public/logo/icons/1024x1024.png" alt="ZCode" width="128" height="128" /> </div> <p align="center"> <a href="https://applink.feishu.cn/client/chat/chatter/add_by_link?link_token=47ag983c-8fcb-4d6d-814b-5395193a712c&amp;qr_code=true">飞书社群</a> · <a href="https://discord.gg/z9aBcQXZQ3">Discord</a> </p> <p align="center"> 简体中文 | <a href="README.en.md">English</a> </p> ZCode 是 AI 编程工作台，提供桌面应用、浏览器界面和终端 Agent。本仓库包含客户端、后端服务、共享 UI，以及 Agent CLI 与运行时源码。 ## 更新 - **2026-10-30**：更新至 ZCode v3.17.1 版本。 - 2026-10-19：更新至 ZCode v3.16.2 版本。

  ZCODE_SERVER_WORKSPACE=/path/to/project pnpm dev:web ``` 该命令同时启动 Web 开发服务器（默认 `http://localhost:5173`）和后端（默认 `http://localhost:3030`）；浏览器访问前者。`/ws` 和一般 `/api` 请求代理到本地后端，`/api/v1/oauth/token` 单独代理到当前配置的产品服务。 Agent 源码修改后，执行 `pnpm --filter @zcode/cli... build` 并重启服务。需要验证完整发行包时，按下方“ZCode 命令行版”打包章节解压运行。 ### ZCode 命令行版 命令行发行包包含 TUI、Web 和 Agent，统一使用 `zcode` 启动：无参数进入 TUI；第一个参数为 `--web` 时启动 Web；其他参数交给现有 Agent CLI 处理。两种模式都在本机运行，无需 Electron。 ```bash # 默认进入终端交互界面 zcode # 启动 Web 界面 zcode --web # 指定项目和端口，不自动打开浏览器 zcode --web --workspace /path/to/project --port 3030 --no-open # 查看 CLI 或 Web 参数

  - 2026-10-16：更新至 ZCode v3.16.1 版本。 - 2026-10-16：更新至 ZCode v3.15.4 版本。 - 2026-10-10：更新至 ZCode v3.15.1 版本。 - 2026-9-23：更新至 ZCode v3.14.3 版本。 ## 初始化 准备 Git、Node.js **24.14.0** 和 pnpm **10.33.2**，版本以 [mise.toml](mise.toml) 为准。以下开发和打包命令均在仓库根目录执行。 ```bash pnpm bootstrap ``` `pnpm bootstrap` 安装 workspace 依赖、准备桌面本地运行资源，再执行 `build:bootstrap`。 Agent CLI 与运行时源码位于 [apps/zcode-cli/](apps/zcode-cli/)，作为普通目录随本仓库一起克隆，无需单独拉取或初始化 Git submodule。 根据需要选择其他初始化或构建入口： | 命令 | 用途 |

  查看 README 缓存打开 GitHub
• jev-chat/jev-chat-jarvisKotlin · 8,200 Stars

  聊天辅助、回复草拟

  Stars 统计更新于 2026/11/1 09:45:54

  查看原始资料

  作者描述

  The chat decision assistant: before you reply, Jev reads the chat, judges intent and risk, and drafts replies you fill in with one tap. You press send. Android · Windows · macOS · iOS | 聊天辅助决策工具：先看懂对方再回复，发不发由你。

  编报时的 AI 中文解读

  jev-chat 是一个聊天辅助决策工具，在回复前先分析对方意图、判断风险并生成回复草稿，用户可一键填入消息框，是否发送由用户决定。适用于在 Android、Windows、macOS 和 iOS 上使用聊天应用的用户。

  编报时的 README 依据

  - **Works where you chat** — WhatsApp, QQ, Feishu and X on Android; chat windows on Windows and macOS; any app through the iOS keyboard - **You press send** — jev-chat only fills the input box and never sends on its own - **Your keys, no server of ours** — requests go only to the model provider you configure, with your own key - **Open source** — MIT licensed, five apps across Android, Windows, macOS and iOS ## Products | Platform | Product | How you use it | Status | | :--- | :--- | :--- | :--- |

  | Android | [Jev for WhatsApp](../global/README.md) (global edition) | Overlay on WhatsApp chats in English | Preview v0.1.0 | | Android | [Jev Chat Assistant](../cn/README.en.md) (Chinese edition) | Overlay on QQ, Feishu, X and WhatsApp | v1.7 | | Windows | [Jev for Windows](https://github.com/jev-chat/jev-chat-windows) | Sits beside your chat window and reads it with screenshots and on-device OCR | Released | | macOS | [Jev for macOS](https://github.com/jev-chat/jev-chat-jarvis-mac) | Overlay that reads the chat on screen and judges with a local model | Released (Apple Silicon) |

  | | Global edition | Chinese edition | | :--- | :--- | :--- | | For | Chats in English on WhatsApp | Chats in Chinese on QQ, Feishu, X and WhatsApp | | Download | [jev-whatsapp-v0.1.0-release.apk](https://github.com/jev-chat/jev-chat-jarvis/releases/download/global-v0.1.0/jev-whatsapp-v0.1.0-release.apk) | [jev-assistant-v1.7-release.apk](https://raw.githubusercontent.com/jev-chat/jev-chat-jarvis/main/cn/apk/jev-assistant-v1.7-release.apk) | | Guide | [Global edition README](../global/README.md) | [Chinese edition README](../cn/README.en.md) |

  1. **Read.** Jev reads the conversation on your screen: through the accessibility service on Android, the chat window on desktop (screenshots with on-device OCR, or system text APIs), and the message you copy on iOS. It does not modify the chat app or log in to it. 2. **Judge first.** Before any reply is written, a judgment model works out what the other person really wants, how risky the moment is and the best way to respond. 3. **Draft, check, rank.** Jev drafts replies, checks them against that judgment and ranks them. Tap one to fill it into the message box. You press send.

  | <img src="../global/docs/images/states/02-decide.png" width="230" alt="Global edition · analysis" /> | <img src="../global/docs/images/states/04-results.png" width="230" alt="Global edition · scored replies" /> | <img src="assets/images/overlay.png" width="230" alt="Chinese edition · overlay" /> | ## Download & Installation ### System Requirements - **Android**: Android 11 or later (the Chinese edition needs an ARM64 phone) - **Windows**: Windows 10 1903 or later, or Windows 11 - **macOS**: macOS 13 or later on Apple Silicon - **iOS**: build it yourself with Xcode ### Android Users

  Download the latest version from the [Releases](https://github.com/jev-chat/jev-chat-jarvis-mac/releases) page. Apple Silicon only. See the [project README](https://github.com/jev-chat/jev-chat-jarvis-mac) for setup. ### iOS Users There is no App Store build yet. Build the keyboard from [source](https://github.com/jev-chat/jev-chat-jarvis-ios) with Xcode. ## How It Works

  > **Use at your own risk:** Using Jev inside third-party apps such as QQ, Feishu, X, or WhatsApp may not comply with those apps' terms of service, and your account could be restricted or banned. Decide for yourself whether to use it. ## Community and Feedback - Problems with the global edition: [report them with the WhatsApp bug template](https://github.com/jev-chat/jev-chat-jarvis/issues/new?template=whatsapp-assistant-bug.md). - Anything else: [open an issue](https://github.com/jev-chat/jev-chat-jarvis/issues).

  查看 README 缓存打开 GitHub
• tamaratran/fast-jev-compactionTypeScript · 7,818 Stars

  上下文压缩、聊天辅助

  Stars 统计更新于 2026/11/1 09:45:53

  查看原始资料

  作者描述

  Claude Code plugin that replaces the compaction summary with Jev decisions: every tool call and result is scored in one fast request, stale ones are dropped or truncated, everything kept stays verbatim.

  编报时的 AI 中文解读

  这是一个Claude Code插件，用于在上下文压缩时用Jev决策替代摘要，保留原始消息，同时也可作为npm库使用。适用于需要精确保留对话历史的Claude Code用户。

  编报时的 README 依据

  # fast-jev-compaction Claude Code plugin that replaces the compaction summary with Jev decisions: every tool call and result is scored in one fast request, stale ones are dropped or truncated, everything kept stays verbatim. Also usable as an npm library. ## What and why Most context compaction asks an LLM to summarize old turns. A summary is lossy: a file path, exact error, constraint, or command can disappear even when it matters later. This library never rewrites anything. It only deletes tool calls and tool results Jev says are no longer needed, and it asks Jev while

  7. The message list is rebuilt: a message that loses all its content is removed, untouched messages are returned as the same objects, and no result is ever left without its call. Jev failures, malformed answers, a missing key, or a history that cannot be fitted throw; the caller (or the Claude Code hook) decides what to fall back to. ## Install and usage ```sh npm install fast-jev-compaction export TYPESAFE_API_KEY=... ``` ```ts import { compactMessages, reductionRatio, type Message } from 'fast-jev-compaction'; const transcript: Message[] = [

  Then add this repository as a plugin marketplace and install the plugin, either from the shell or as slash commands inside a session: ```sh claude plugin marketplace add tamaratran/fast-jev-compaction claude plugin install fast-jev-compaction@fast-jev-compaction ``` The install prompts for the plugin options (API key, thresholds, `truncateHeadChars`, …); leave them at their defaults to use `TYPESAFE_API_KEY` from the environment. Restart Claude Code or run `/reload-plugins`. From then on `/compact` (and auto-compaction) goes through Jev: the toast reads

  is a thin adapter that feeds `session.compact` transcripts through `src/` and falls back to Claude Code's built-in summary on errors or insufficient reduction. See [`hooks/README.md`](hooks/README.md) for configuration and the Claude Code 2.1.274 type reference. ### Install in Claude Code Function hooks are an early-access Claude Code feature (2.1.274+), so the opt-in flag must be set wherever Claude Code runs, e.g. in `~/.claude/settings.json`: ```json { "env": { "CLAUDE_CODE_ENABLE_FUNCTION_HOOKS": "1", "TYPESAFE_API_KEY": "<your key>" } } ```

  | `maxStateTokens` | `25000` | Estimated token ceiling for the state | | `maxRequestTokens` | `30000` | Estimated ceiling for state plus one batch of questions | | `truncateHeadChars` | `300` | Characters of a dropped tool result retained before its note | `result.stats` reports message and character counts before and after, the per-reason decision counts, the state size in estimated tokens, which fitting stage was needed, and the number of requests. ## Limitations - Only tool calls and results are candidates; text messages are never removed

  or shortened in the output (they are only abridged in the state Jev sees). - Token sizes are estimates from character counts, not a tokenizer. - Calibration is at the request level; a probability is not a proof that a result is safe to delete. The assistant can always re-run the tool. - The full state is repeated with every request, so a history near the state ceiling costs one request per handful of questions. ## Claude Code plugin The repository root is a Claude Code function-hook plugin: `hooks/fast-jev.ts`

  查看 README 缓存打开 GitHub
• yi1108/printfilmPython · 7,385 Stars

  视频剪辑、图像编辑、音频编辑

  Stars 统计更新于 2026/11/1 09:31:01

  查看原始资料

  作者描述

  PRINTFILM: AI short-video marketing and AI short-drama creation platform

  编报时的 AI 中文解读

  PRINTFILM 是一个 AI 短视频和 AI 漫剧创作平台，支持从文案、分镜到成片的完整流程，并提供独立生成工具和管理后台。适合需要制作营销短片、漫剧或单张图片/视频的创作者和团队。

  编报时的 README 依据

  | `ark_mock: true` | 关掉 `ARK_MOCK`，并确认 Key 非空后 `--force-recreate api` | | 401 / 额度不足 | 到 TokenFree 控制台看 Key 是否启用、余额是否够 | | 模型名 404 | 在后台模型列表里选 TokenFree 实际提供的模型 id | ## 适用场景 - 短视频 / 获客片：把卖点做成可投放的短片 - 漫剧 / 短剧：从大纲到分集，角色场景保持一致 - 单点出图出片：工具中心直接生成 - 自托管：Docker 拉镜像即可在自己的机器上跑 ## 目录结构 ``` backend/ FastAPI、流水线、计费、任务运行时 frontend/ 用户端 admin/ 运营后台 deploy/ 环境变量示例、中间件 compose docs/ 规范与专题文档 docker-compose.yml 拉公开镜像一键启动 docker-compose.full.yml 从源码构建 ``` ## 社区 - GitHub：https://github.com/yi1108/printfilm

  本机只需安装 [Docker Desktop](https://www.docker.com/products/docker-desktop/)（或 Docker Engine + Compose）。镜像在阿里云 ACR `gcc` 公开命名空间，**拉取无需登录**。 ### 1. 克隆并准备环境变量 ```bash git clone https://github.com/yi1108/printfilm.git cd printfilm cp deploy/.env.docker.example deploy/.env.docker ``` 编辑 `deploy/.env.docker`，至少改这三项： | 变量 | 说明 | |------|------| | `POSTGRES_PASSWORD` | 数据库密码（勿用示例默认值） | | `SECRET_KEY` | 任意长随机串（会话 / 密钥加密） | | `OPENAI_API_KEY` / `ARK_API_KEY` | TokenFree API Key（同一把填两处即可） | 无 Key 想先看界面：把 `ARK_MOCK=true`。 ### 2. 一键启动 ```bash docker compose --env-file deploy/.env.docker up -d ```

  等约半分钟（API 健康检查通过后，web / admin 才会起来）。 | 服务 | 地址 | |------|------| | 用户端 | http://localhost:8080 | | 管理后台 | http://localhost:8081 | | API / 文档 | http://localhost:8000 · `/docs` | | 健康检查 | http://localhost:8000/api/health | 常用： ```bash docker compose --env-file deploy/.env.docker ps # 状态 docker compose --env-file deploy/.env.docker logs -f api # 看日志 docker compose --env-file deploy/.env.docker down # 停止（保留数据卷） ``` ### 3. 注册与管理员 | 角色 | 怎么拿 | |------|--------| | 普通用户 | 打开用户端 → `/auth` 邮箱注册 |

  | 管理员 | 先用该邮箱注册 → 在 `.env.docker` 设 `ADMIN_BOOTSTRAP_EMAILS=你的邮箱` → `docker compose --env-file deploy/.env.docker up -d --force-recreate api`（**只提权，不造号**） | 仓库无内置演示账号；生产请立刻改掉密钥。 ### 4. 更新到最新镜像 ```bash docker compose --env-file deploy/.env.docker pull docker compose --env-file deploy/.env.docker up -d ``` ### 5. 从源码构建（可选） 改过前后端代码，或拉不到 ACR 时： ```bash docker compose --env-file deploy/.env.docker -f docker-compose.full.yml up -d --build ``` ## 配置 TokenFree API Key 开源版文字 / 图 / 视频统一走 **TokenFree New API**（OpenAI 兼容：`https://www.tokenfree.com/v1`）。没有 Key 时只能 `ARK_MOCK=true` 看界面，不能真实生图 / 生视频。

  查看 README 缓存打开 GitHub
• mizorewww/laya-mlxPython · 7,053 Stars

  模型本地部署、模型接口服务

  Stars 统计更新于 2026/11/1 09:40:49

  查看原始资料

  作者描述

  Native MLX runtime for Laya typed decision models — 7–14 ms short decisions on M3 Max. No text generation, PyTorch, or cloud API.

  编报时的 AI 中文解读

  在 Apple Silicon 上原生运行 Laya 类型化决策模型的工具，用于快速回答受限问题（如选项选择、评分、真伪判断），无需生成文本或调用云端 API。

  编报时的 README 依据

  Requires Apple Silicon, macOS 14+ and Python 3.11+. ```bash pip install laya-mlx ``` ```python import laya_mlx as laya agent = laya.load("aac6fef/laya-mlx") result = agent.predict( "I was billed twice. Please refund the duplicate.", { "department": { "type": "choice", "instructions": "Which department should handle this request?", "criteria": { "billing": "Payments, invoices, refunds, and duplicate charges.", "technical": "Broken features, errors, and product troubleshooting.",

  - **Confidence gate:** `min_confidence=` marks low-confidence answers for review without changing them. - **Large choice sets:** `predict_shortlist` (embedding pre-filter) and `predict_tournament` (no embedder). - **Throughput options:** `compile=True`, `pad_to_multiple=16` and `cache_prompts=True` for repeated workloads. - **Tools and services:** CLI (`laya-mlx predict`), HTTP (`laya-mlx-serve`), MCP (`laya-mlx-mcp-server`), evaluation and calibration, and LangChain/LlamaIndex/CrewAI/Agno integrations, installed as extras. - **Export:** `laya-mlx convert` writes a standalone MLX checkpoint.

  [optimization](https://github.com/mizorewww/laya-mlx/blob/main/docs/SNAKE_OPTIMIZATION.md). ## Relationship to upstream This is an independent port, not an official Convai Innovations release. Prompt formatting, calibration, routing, output schema and host APIs follow [NandhaKishorM/laya](https://github.com/NandhaKishorM/laya) **v0.4.17**; the encoder and decision heads are reimplemented in MLX. CUDA, ONNX, PyTorch backend controls and training are out of scope. RLCD training and fine-tuning stay upstream.

  查看 README 缓存打开 GitHub
• Mak5er/AirCardSwift · 6,960 Stars

  钱包卡面美化、锁屏主题制作

  Stars 统计更新于 2026/11/1 09:45:52

  查看原始资料

  作者描述

  Apple Wallet Card Skinner for iOS 18+ (No Jailbreak Required)

  编报时的 AI 中文解读

  AirCard 是一款 macOS 应用，用于自定义 Apple Wallet 卡面外观和锁屏密码键盘主题，支持 iOS 18 及以上版本，无需越狱。

  编报时的 README 依据

  > AirCard uses macOS native Python 3 (`/usr/bin/python3`). If macOS prompts that Developer Tools are required or if you recently installed/updated Xcode: > - Install Command Line Tools: `xcode-select --install` > - Accept Xcode license if applicable: `sudo xcodebuild -license accept` > [!NOTE] > **Windows users:** an unofficial Windows port is available at [**AirCard-Windows**](https://github.com/Lumid-Off/AirCard-Windows). --- ## How to Customize Apple Wallet Cards 1. Connect your iPhone to your Mac via USB cable and ensure it is unlocked and trusted.

  2. In AirCard, stay on the **Wallet Cards** tab and click **Scan Cards**. 3. On your iPhone: - **Double-click the Side (Power) button** to open Apple Pay. - Authenticate with **Face ID**. - **Tap your card** (or tap it once more) to trigger instant detection! 4. Click on any card mockup or drag & drop an image directly onto the card. 5. Click **Flash Skins**. 6. Force-close the **Wallet** app on your iPhone from the App Switcher (or reboot) to see your new custom card design! > [!NOTE] > **Apple Card:**

  device logs or card identifiers. See [scanner validation](docs/wallet-card-detection.md) for the verified environment and remaining coverage. --- ## How to Apply Lockscreen Passcode Themes (.passthm) 1. Switch to the **Passcode Themes** tab at the top of AirCard. 2. Drag & drop any `.passthm` file into the app (or click **Choose .passthm File**). 3. AirCard will inspect the theme and display an interactive preview on the numeric keypad (0–9, *, #). 4. Click **Apply Passcode Theme**. 5. Restart your iPhone to reload the lock screen cache and see your custom passcode buttons! > [!TIP]

  - ⚡ **Per-Card & Bulk Customization:** Set unique artwork for each card or apply one design across all cards with a single click. - 📱 **Zero-Hassle Card Detection:** Tap any card in your iPhone's Wallet app to detect its hash in real-time. - 🚀 **100% Standalone (Universal):** Native support for both **Apple Silicon** and **Intel (x86)** Macs. All required device-communication utilities and image engines are pre-bundled inside the app. - 📦 **Zero Prerequisites:** No Homebrew, Python packages, or terminal setup required for macOS users. --- ## Guides and sample artwork

  | **iOS 18.0 – 27.0.1** | ✅ Supported | Full support for Wallet skins and Lockscreen passcode themes | | **iOS 27.2 beta 1 – beta 2** | ✅ Supported | Working | | **iOS 27.2 beta 3+** | ❌ Patched | Apple patched the underlying `airlift` exploit. Flashing will not work. | > [!IMPORTANT] > Do not update to **iOS 27.2 beta 3 or newer** if you want to continue using AirCard. The underlying AirTraffic sync exploit was patched by Apple in beta 3. --- ## Features - 🎨 **Custom Card Skins:** Assign custom artwork, textures, or bank logos to Apple Pay and Wallet cards.

  > The Apple Card (titanium/digital card) uses dynamic vector rendering based on your spending categories instead of static cached card skins. Custom skins apply to standard debit/credit cards, transit cards, and passes. ### Card names and missing-card checks Scanned cards can now display names from this Mac's Wallet cache. Open **Check missing cards** to distinguish current-scan matches from membership entries and payment caches that still need confirmation. Use **Reconnect** for connection problems and **Read Cache** to reread local metadata.

  查看 README 缓存打开 GitHub
• Louis-CFM/coucouSwift · 6,846 Stars

  AI代理监控、语音听写、通话记录

  Stars 统计更新于 2026/11/1 09:40:51

  查看原始资料

  作者描述

  A tiny friend in your Mac's notch and on your iPhone that keeps an eye on your AI coding agents: Claude Code, Codex, Cursor, Gemini CLI, Antigravity and more. Approve from the notch or your Lock Screen.

  编报时的 AI 中文解读

  Coucou 是一个跨平台桌面应用，在 Mac 的刘海、Windows/Linux 屏幕顶部以及 iPhone/Android 上显示一个名为 Mochi 的可爱角色，用于监控 AI 编程代理会话，支持权限审批、聊天、语音听写、通话记录等功能。

  编报时的 README 依据

  <div align="center"> <img src="NotchBuddy/Assets.xcassets/AppIcon.appiconset/icon_256x256.png" width="96" alt="Coucou icon"> # Coucou **A tiny friend that lives in your Mac's notch — or at the top of your screen on Windows and Linux — and keeps an eye on your AI coding agent sessions. And now on your phone too: iPhone and Android.** Approve permissions, watch your agents work, drop a file, chat with Claude — all without leaving what you're doing. Walk away from your Mac and Mochi follows you to your iPhone: Lock Screen, Dynamic Island, widgets, Siri.

  **New in 0.4: Coucou is a real Mac app.** Hold a key anywhere, speak, let go: your words are pasted where you type, like Wispr Flow — free, open source, and offline with Parakeet. Record your calls without a bot in the meeting and get the transcript, the summary and the to-dos. [](https://github.com/Louis-CFM/coucou/releases)  

  - ⌨️ **Keyboard shortcuts** — open the chat, jump to an alert or a terminal, switch pills, mute, send Mochi to the desktop or open the wardrobe from anywhere; all customizable in Settings → Shortcuts. - 🎭 **A real character** — idle breathing, blinks, eyes on a sphere that follow your mouse, emotes, 28 handcrafted sounds, a greeting on launch. - 🔊 **Your own sounds** *(macOS)* — drop a file named like one of Mochi's sounds (`finish.wav`, `approval.mp3`…) in Settings → General → Sound → **Open sounds folder** to replace it.

  - 🗣️ **« OK Coucou »** *(macOS, GitHub build)* — talk to Mochi like Jarvis. Say « OK Coucou », then ask: « how much did I make on Stripe today? », « swap GitHub for Stripe », « play some Daft Punk », « who won the game last night? », « send an email to Enzo to tell him the image is ready ». Claude is the brain (your own Anthropic API key, set in Settings → Chat); speech recognition runs on your Mac, and only your words and the data Coucou reads to answer go to Anthropic, never audio. Mochi listens, thinks and answers out loud; emails open in the notch and leave only when you click Send.

        

  - 💊 **The pill** — a small see-through pill at the bottom of the screen (or on its left or right edge). Hover it for a toolbar: dictate, record a call, open Coucou. While you speak, Mochi listens and nine dots follow your voice. - 🦜 **Parakeet, offline** — run NVIDIA's Parakeet on your Mac's Neural Engine through [FluidAudio](https://github.com/FluidInference/FluidAudio): more accurate, 25 languages, nothing leaves your Mac. One click to download (about 650 MB), Apple silicon only. Until then the Mac's own recognition is used.

  <td width="33%"><img src="docs/media/hub-statistics.png" alt="Statistics: words dictated, time saved, speed, words per day and where you dictate"></td> <td width="33%"><img src="docs/media/hub-styles.png" alt="Styles: an optional clean-up by Claude, as said, natural or polished, per app"></td> <td width="33%"><img src="docs/media/hub-settings.png" alt="Settings: the key to hold, where the pill is, hands-free, paste again and cancel"></td> </tr> </table> Flow dictation and the Notetaker are on the Mac for now; Windows and Linux are next. ## Features

  **Status:** tested on a real phone (Android 13) with the Windows app. The phone link is in **Coucou 0.4.0 for Windows and Linux**. Download the signed APK from the [latest Android release](https://github.com/Louis-CFM/coucou/releases/tag/android-v0.3.0). Android needs Coucou on **Windows or Linux** (not the Mac), Android 11 or later, and both on the same Wi-Fi. Full guide: [`android/README.md`](android/README.md). <table> <tr> <td><img src="docs/media/claude-code.png" alt="Claude Code session"></td> <td><img src="docs/media/stripe.png" alt="Stripe payments"></td> </tr> <tr>

  查看 README 缓存打开 GitHub
• Jakeschincariol/replica-skillPython · 6,826 Stars

  应用克隆、逆向工程、应用测试

  Stars 统计更新于 2026/11/1 10:25:49

  查看原始资料

  作者描述

  Eleven free Claude skills that clone any app: reverse-engineer it, rebuild it, test it for bugs, then fix what its users hate. Free, MIT.

  编报时的 AI 中文解读

  提供11个Claude技能，用于克隆任何应用：逆向分析、重建、测试、修复用户痛点，并完成品牌、上线和部署。适合希望快速构建竞品应用的开发者或创业者。

  编报时的 README 依据

  **It rebuilds what an app does, never what it owns.** Features and flows, clean-room style. Not its code, its logo, its copy or its content. The fine print is at the bottom, and the skills enforce it. ## Install Paste this into Claude: ``` https://github.com/Jakeschincariol/replica-skill install skill ``` Or as a plugin, in Claude Code: ``` /plugin marketplace add Jakeschincariol/replica-skill /plugin install replica-skill@replica-skill ``` Claude Code namespaces plugin skills, so installed as a plugin they show up as

  `/replica-skill:replica-recon` and so on. Copy the folders instead if you want plain `/replica-recon`: ```bash git clone https://github.com/Jakeschincariol/replica-skill.git cp -r replica-skill/replica-* ~/.claude/skills/ ``` Project-local instead of global: copy the same folders into your repo's `.claude/skills/`. No Claude Code at all? Paste any single `SKILL.md` at the top of a chat and it runs as a mode. You lose the Python tools, but the method works. The tools need Python 3.8 or newer. Nothing to pip install. ## The eleven | command | what it does | | --- | --- |

  **It always rebrands before launch.** New name, new palette, new logo, new words. `/replica-deploy` will not ship until the sweep is clean. **"Clone any app" means the features and the flow.** Not the content, the network or the licences an app owns. You can rebuild a music app's player, playlists and sharing. You cannot clone its catalogue. **No guarantee of a "perfect" clone.** Results depend on how complex the app is. A booking tool is weeks. A spreadsheet engine is not. `/replica-recon` sizes it honestly before you start, and `/replica-diff` gives you a real number, not a vibe.

  查看 README 缓存打开 GitHub
• CopilotKit/OpenDotsTypeScript · 6,267 Stars

  AI代理工作区、网页自动化、聊天辅助

  Stars 统计更新于 2026/11/1 09:50:55

  查看原始资料

  作者描述

  Your always-on AI coworkers that move between text, calls, and Slack.

  编报时的 AI 中文解读

  OpenDots 是一个开源的 AI 代理工作区模板，用于构建持久化的 AI 同事，可在文本、通话和 Slack 中工作。它提供 Spaces 工作区、专家 Dots、浏览器控制等功能，适合希望自托管并定制 AI 代理工作流的开发者。

  编报时的 README 依据

  [OpenMuse](https://github.com/CopilotKit/OpenMuse) and [OpenBot](https://github.com/CopilotKit/openbot) are code references for persistent work, agent computers, and execution controls. OpenDots can be adapted to your own workflows and deployment choices. ## Get started Use **Node.js 24** and **npm**: ```sh git clone https://github.com/CopilotKit/OpenDots.git cd OpenDots npm ci cp .env.example .env npm run dev ```

  Open **http://127.0.0.1:5173**. You can create Spaces, write pages, and configure Dots before connecting services. To start chatting, connect an Intelligence project and a model. Choose where to store conversations before connecting. For local Docker evaluation, follow [Local Intelligence evaluation](docs/SETUP.md#local-intelligence-evaluation). For hosted Intelligence, sign in and select or create a project in the `OpenDots` folder: ```sh npx copilotkit@latest login npx copilotkit@latest project select ```

  `project select` writes a project key to `.env` as `CPK_INTELLIGENCE_API_KEY`. Keep the generated `CPK_TELEMETRY_ID` with that key so SDK usage can resolve to your Intelligence account. Then add `OPENAI_API_KEY` and `OPENAI_MODEL` to `.env` and restart `npm run dev`. Do not run `copilotkit onboard` in this folder. OpenDots already contains its CopilotKit integration, and onboarding adds a second, generic one. See [Setup](docs/SETUP.md) for configuration, Slack, calls, the browser service, and Docker. ## Data and privacy

  This is a single-owner starting point. Shared editing, invitations, file uploads, and interactive page embeds are not included. Schedules are recurring instructions, not a complete goal or event-trigger system. Specialist Dots have separate roles and conversations; multi-Dot group conversations and automatic delegation are further work. ### Extending the template - Add identity, Space membership, and shared page editing for multi-user deployments. - Add file attachments and richer page content. - Add event triggers and a persistent responsibility lifecycle.

  查看 README 缓存打开 GitHub
• CopilotKit/openmuseTypeScript · 6,028 Stars

  网页自动化、任务管理、PDF处理

  Stars 统计更新于 2026/11/1 10:20:59

  查看原始资料

  作者描述

  A personal agent with a browser, terminal, files, and work that keeps going built with CopilotKit and AG-UI.

  编报时的 AI 中文解读

  OpenMuse 是一个个人代理应用，集成了浏览器、终端、文件管理和持久化任务执行，支持 iOS、Android 和 Web 平台，适合需要自动化完成复杂任务的个人用户。

  编报时的 README 依据

  ## Quick start **Requirements:** Node 24 LTS, pnpm 11.19.0, and a CopilotKit Intelligence project key. The local sample app needs no model, Google account, or Docker. ```sh git clone https://github.com/CopilotKit/OpenMuse.git openmuse cd openmuse pnpm install --frozen-lockfile cp .env.example .env npx copilotkit@latest login npx copilotkit@latest project select # Set CPK_INTELLIGENCE_API_KEY in .env to the generated server-only project key. # Keep the CLI-generated CPK_TELEMETRY_ID too, including in deployed server environments. pnpm dev ``` In another terminal: ```sh pnpm dev:web ```

  Open [localhost:8081](http://localhost:8081). The API runs at [localhost:8787/api/health](http://localhost:8787/api/health). ### Try it 1. In Chat, send **“Complete the permission slip”**. Open the task, supply fictional form values, inspect the saved PDF, and review the prepared reply. This writes only to the local mailbox. 2. In **Goals → Track**, create a built-in availability watch, then change the built-in test page to trigger an alert. 3. In **Menu → Delegate task → Finance**, use **Try example transactions** to create an interactive spending tracker.

  OpenMuse is a personal-agent application with an agent computer, visible work, and rich results. It runs its own server, task worker, and browser worker. You can inspect and change the source under the MIT license. The computer combines **persistent Chromium and an optional Linux workspace**. The agent can browse public pages, run commands in its own container, work with files, and move PDFs between the computer and the app. You can open its browser or terminal and continue the work. Graphical desktops and autonomous checkout remain future work. ## Features

  查看 README 缓存打开 GitHub
• alchaincyf/huashu-art-motionJavaScript · 5,864 Stars

  艺术动画生成、风格化动画、解说视频制作

  查看原始资料

  作者描述

  艺术动画skill：35种艺术风格、9种解说语法，用代码让画动起来。

  编报时的 AI 中文解读

  这是一个面向AI编码代理的Skill，用于通过代码生成艺术动画，包含多种艺术风格和动画语法，适合希望用代码创作动态画作的开发者。

  查看 README 缓存打开 GitHub
• shader-effects-inc/shadersTypeScript · 5,735 Stars

  WebGPU特效、可视化设计

  查看原始资料

  作者描述

  WebGPU components for React, Vue, Svelte, Solid, JS & Framer

  编报时的 AI 中文解读

  Shaders 是一个提供 WebGPU 特效组件的库，支持 React、Vue、Svelte、Solid 和 JavaScript，包含 200 多个效果组件，并配有可视化设计编辑器和 CLI 工具。

  查看 README 缓存打开 GitHub
• omlahore/RemoveMacAISwift · 5,659 Stars

  系统精简

  查看原始资料

  作者描述

  Debloat macOS: turn off Apple Intelligence, analytics, ads and pop-ups. A native app and CLI, and every change can be undone.

  编报时的 AI 中文解读

  用于精简 macOS 系统的原生应用和命令行工具，可关闭 Apple Intelligence、分析、广告和弹窗，所有更改可撤销。

  查看 README 缓存打开 GitHub
• Supermedo/bloodborne_pcC++ · 4,985 Stars

  游戏启动器、画质增强、作弊与Mod

  查看原始资料

  作者描述

  Bloodborne running natively on Windows 10/11: launcher in 13 languages, DLSS, FSR 3.1/4, unlocked FPS, cheats, mods, one-click updates.

  编报时的 AI 中文解读

  让《血源诅咒》原生运行在Windows 10/11上的启动器与游戏移植，提供中文等13种语言界面、DLSS/FSR等画质增强、解锁帧率、作弊、Mod支持及一键更新。适合拥有正版游戏dump的玩家在PC上体验。

  查看 README 缓存打开 GitHub
• QingYunA/answer-me-with-htmlJavaScript · 4,975 Stars

  HTML回答生成、网页自动化

  查看原始资料

  作者描述

  Answer me with HTML — an agent skill that answers hard questions with a one-page HTML you can actually read. 让 AI Agent 用一页 HTML 回答复杂问题。

  编报时的 AI 中文解读

  这是一个Agent技能，让AI Agent用一页可读的HTML回答复杂问题，而不是输出大段文本。它通过CLI将Markdown草稿快速渲染成包含图表、表格、代码的页面，适合需要清晰阅读和分享答案的用户。

  查看 README 缓存打开 GitHub
• TheoLeeCJ/SemIf-OpenJevPython · 4,915 Stars

  语义决策、模型本地部署

  查看原始资料

  作者描述

  Semantic ifs from open models, on a 3090 at home. Independent; not affiliated with Jev or TypeSafe.

  编报时的 AI 中文解读

  SemIf 是一个独立研究项目，用开放模型在本地（如 RTX 3090）实现运行时定义的语义决策，直接读取类型化选项的概率，无需生成文本。适合需要快速、可审计决策的开发者或研究者。

  查看 README 缓存打开 GitHub
• nykooi1/vibe-wisePython · 4,089 Stars

  AI辅助编程、学习编程

  查看原始资料

  作者描述

  A Claude Code / Codex plugin that helps you learn how to build while AI writes the code.

  编报时的 AI 中文解读

  VibeWise 是一个用于 Claude Code 和 Codex 的插件，旨在让用户在 AI 编写代码的同时学习编程。它通过要求用户先描述方法、检查权衡并解释不熟悉的概念，让用户保持对设计的控制。适用于希望在构建中学习的初学者、初级开发者和探索新栈的经验丰富的工程师。

  查看 README 缓存打开 GitHub
• nullmoth/nvidia-macos-driverRust · 3,957 Stars

  驱动安装、系统兼容、硬件加速

  查看原始资料

  作者描述

  Metal driver for NVIDIA GeForce cards on macOS Sequoia

  编报时的 AI 中文解读

  为 macOS Sequoia 上的 NVIDIA GeForce 显卡提供 Metal 驱动，支持 Turing 及更新架构的显卡，适用于 Intel Mac 和 OpenCore 组装机。

  查看 README 缓存打开 GitHub
• designfuchen/word-atlasTypeScript · 3,568 Stars

  雅思背词、间隔复习、词库下载

  查看原始资料

  作者描述

  词光 · Word Atlas — Illustrated IELTS vocabulary with 7,298 words, UK/US audio and FSRS review. Open-source app + CC BY 4.0 dataset.

  编报时的 AI 中文解读

  词光是一款以插画和语境为核心的雅思背词应用，提供7,298个词条、原创插画、英美发音和FSRS间隔复习，无需账号，学习进度保存在本地设备上。

  查看 README 缓存打开 GitHub
• JoasASantos/REA-PromptsBatchfile · 3,352 Stars

  逆向工程提示词、软件分析

  查看原始资料

  作者描述

  REAP - Prompts for you to use REA (Reverse Engineer Anything), get the most out of it, and clone or break down any program

  编报时的 AI 中文解读

  为REA逆向工程工具集提供一套精选提示词，帮助AI编码代理分析软件工作原理，涵盖从原生二进制、固件、内核到游戏、Electron应用、APK和网站等多种目标。

  查看 README 缓存打开 GitHub
• alejandrobujan/tendederoSwift · 2,840 Stars

  截图管理

  查看原始资料

  作者描述

  Screenshots, hung out to dry. A tiny native macOS app that hangs every screenshot on a line at the top of your screen.

  编报时的 AI 中文解读

  Tendedero 是一款 macOS 原生应用，将截图悬挂在屏幕顶部的一条线上，方便快速访问和管理，支持点击复制、拖拽分享、标记等操作。

  查看 README 缓存打开 GitHub
• facebookincubator/muse-gadget-sdkC · 2,533 Stars

  硬件开发、设备配对

  查看原始资料

  作者描述

  Open source SDK to build Muse gadgets

  编报时的 AI 中文解读

  Muse Gadgets 是一套开源 SDK 和固件，用于将 ESP32 开发板或 Raspberry Pi 等设备变成 Muse 的硬件配件，可连接屏幕、按钮、传感器等，并通过 Muse 应用配对控制。

  查看 README 缓存打开 GitHub
• LoreanXavier/pt-pcC++ · 2,328 Stars

  游戏移植

  查看原始资料

  作者描述

  Native PC port of P.T. (runs from your own PS4 game files)

  编报时的 AI 中文解读

  这是一个将2014年PS4游戏P.T.移植到PC的原生版本，需要玩家自备PS4游戏文件才能运行。它面向希望在现代PC上重温该游戏的玩家，支持Windows、Linux和macOS。

  查看 README 缓存打开 GitHub
• noahdunnagan/fsearchRust · 2,211 Stars

  文件搜索、内容检索、AI辅助编程

  查看原始资料

  作者描述

  Whole-disk file search for macOS: fuzzy names, typo tolerance, indexed content grep. ~1 ms over 8M files.

  编报时的 AI 中文解读

  FSearch 是一款面向 macOS 的整盘文件搜索工具，支持模糊文件名匹配、拼写容错以及基于索引的文件内容搜索。它提供命令行界面、后台守护进程、Rust 库和 MCP 服务器，适用于开发者和需要快速定位文件的用户。

  查看 README 缓存打开 GitHub
• kargulstudio/sales-crmTypeScript · 1,847 Stars

  项目启动模板

  查看原始资料

  编报时的 AI 中文解读

  基于 Next.js 16、React 19 和 Tailwind CSS 4 的项目启动模板，内置开发、构建、lint 等脚本，并附带图片和动画资源处理工具。适合需要快速搭建 Next.js 应用的开发者。

  查看 README 缓存打开 GitHub
• sganggs/Stronghold-ProtocolJavaScript · 1,818 Stars

  游戏复刻、联机合作

  查看原始资料

  作者描述

  明日方舟「卫戍协议：盟约」非官方同人复刻：浏览器自走棋塔防，单人或 1–4 人联机合作（非商业）

  编报时的 AI 中文解读

  这是一个非官方的明日方舟同人复刻，在浏览器中实现自走棋塔防玩法，支持单人游戏或1至4人联机合作。适合喜欢明日方舟和自走棋塔防的玩家，用于学习交流和个人娱乐。

  查看 README 缓存打开 GitHub
• Caho1/open-claude-uiTypeScript · 1,608 Stars

  UI组件库、动效引擎、逆向分析手册

  查看原始资料

  作者描述

  基于 REA 深度拆解并高保真还原 Claude 官方桌面端 UI。还原 30 个独立 React 组件与 8 项硬核交互物理算法，附带 3000+ 行逆向分析手册。

  编报时的 AI 中文解读

  基于逆向工程的高保真开源 UI 组件库与动效引擎，还原 Claude 桌面端设计系统与交互物理，附带深度技术手册，供前端开发者与 AI Agent 使用。

  查看 README 缓存打开 GitHub
• marclou/mailcheapJavaScript · 1,587 Stars

  新闻通讯发送、订阅者管理、邮件统计

  查看原始资料

  作者描述

  Newsletters where you pay for the emails you send, not for dormant subscribers, at a fraction of the price of beehiiv and the like. Open source: self-host it, or use mailcheap.ai.

  编报时的 AI 中文解读

  MailCheap 是一个开源的自托管或云托管的新闻通讯应用，支持撰写、审核、发送邮件，并提供订阅者管理、统计和网站发布功能。适合需要控制发送成本、注重邮件送达率的个人或团队。

  查看 README 缓存打开 GitHub
• rociiu/talorysTypeScript · 1,430 Stars

  聊天辅助、任务管理、定时提醒

  查看原始资料

  作者描述

  Your personal AI agent in your own Cloudflare account. Chat, memory, tasks, notes and scheduled reminders, deployed with one command: npx create-talorys@latest. Free-tier friendly, single-user, no telemetry.

  编报时的 AI 中文解读

  Talorys 是一个部署在用户自己的 Cloudflare 账户中的个人 AI 助手，提供聊天、记忆、任务、笔记和定时提醒功能，适合希望数据自主掌控的单用户使用。

  查看 README 缓存打开 GitHub
• mizorewww/x_gift_botGo · 1,284 Stars

  礼品兑换、订单管理

  查看原始资料

  作者描述

  X Premium gift CLI and redemption site

  编报时的 AI 中文解读

  X (Twitter) Premium 礼品兑换平台，用于生成兑换码并让用户自助兑换，系统自动完成 Premium 赠送的下单与付款。适用于需要批量赠送 X Premium 的运营者或商家。

  查看 README 缓存打开 GitHub

其余 890 个项目见收录列表。

查看本期全部收录项目