Intuition-Lab
personal-model
Persome is an open-source tool that builds a private, local personal model on macOS from captured activity and provides evidence-linked context to MCP-compatible AI agents like Codex and Claude Code.
AI 仓库情报摘要
FR-AI / ANALYSIS为什么值得关注
它采用基于 Rust 的 RaptorQ 喷泉码和 fast_qr 渲染库编译为 WASM，相比之前的 QR 流式传输原型吞吐量提升至少 50 倍，达到可用于生产环境的离线传输水平。
适合谁使用
- 需要快速、离线设备间传输的开发者
- 在隔离或安全环境中工作的 IT 专业人员
- 常在没有网络或数据线情况下共享文件的用户
- 探索创新型 QR 通信技术的爱好者
典型使用场景
- 在两部手机或手机与电脑之间无需网络传输文档
- 通过终端（CLI）向手机摄像头发送文本或文件
- 在蓝牙或 Wi-Fi 不可用或受限的环境中快速共享文件
- 在教育或技术演示中展示高速 QR 数据流
项目优势
- 实测吞吐量比纯 JavaScript QR 流式传输提升 50 倍以上
- 完全离线且支持 PWA，无上传服务器确保隐私安全
- 采用 Rust 实现的 RaptorQ 和 fast_qr 编译为 WASM，实现高性能编码与渲染
- 可调节 QR 版本、纠错等级、帧率和修复开销，兼顾速度与可靠性
使用前须知
- 传输速度严重依赖设备摄像头质量、光线条件和浏览器性能
- 接收端必须使用 RaptorQR Web 应用（或核心库），终端 CLI 仅支持发送
- 大文件（如 6.5 MB）即使最优设置仍需数十秒
README 快速开始
RaptorQR
The world's fastest files and texts transfer between devices by displaying high-throughput animated QR codes and reading them with a camera.
Everything runs locally in the browser or terminal: no upload server, no Bluetooth, no cable.
RaptorQR started from an earlier open-source QR streaming prototype and has since become a substantial rewrite of the core transfer pipeline and user experience: FEC, QR rendering, worker scheduling, scanner integration, sender/receiver UI, CLI packaging, and the repo layout have all been rebuilt around a higher-throughput, production-ready architecture.
Live demo: https://qr.linkto.host/
Table of Contents
- Performance
- Packages
- Features
- FAQ
- Development
- CLI
- WASM Artifacts
- Implementation Notes
- Links & Acknowledgements
Performance
RaptorQR uses the Rust cberner/raptorq implementation of RaptorQ (RFC 6330), compiled to WASM, as its primary fountain-code codec. This project also compiles erwanvivien/fast_qr to WASM for high-speed QR rendering, with a more feature-complete wrapper than the upstream WASM package, and uses ZXing WASM for scanning.
The result is a massive performance improvement over the original JavaScript-only transfer path. In measured tests, the new pipeline reaches at least 50x+ higher throughput in practical transfer scenarios.
Measured examples:
| Scenario | Result |
|---|---|
| V20 QR, 4-code parallel playback, 30 FPS | up to 300 decoded QR symbols/s |
| V30 QR, 4-code parallel playback, 30 FPS | 100+ decoded QR symbols/s |
| 95.2 KB file transfer (V30-L x 4QR@30fps) | 375 ms, about 254.0 KB/s |
| 6.5 MB file transfer (V30-L x 4QR@30fps) | 36 s, about 183.6 KB/s |
The 95.2 KB and 6.5 MB file tests were measured on iPhone 16 / Safari as QR scanner as 'lab results'. Actual speed depends on device came
项目描述
Ultra-fast offline file and text transfer over animated QR codes with WASM fast_qr, ZXing and RaptorQ.
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