Working on firmware 1.7.2 NOTE: there might still be issues with some features of Netbird, but this at least gets it up and running and connected.
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A pattern for building personal knowledge bases using LLMs.
This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.
Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.
本文基于 Frost Ming “friendly python” 标签下的文章，整理出偏向工程实践的开发范式、规范与典型好/坏代码范式示例。重点是“对使用者友好 + 对维护者友好”，并强调在 Python 中利用语言特性与生态扩展点进行合理抽象。
Modern versions of Windows support GPU paravirtualization in Hyper-V with normal consumer graphics cards. This is used e.g. for graphics acceleration in Windows Sandbox, as well as WSLg. In some cases, it may be useful to create a normal VM with GPU acceleration using this feature, but this is not officially supported. People already figured out how to do it with Windows guests though, so why not do the same with Linux? It should be easy given that WSLg is open source and reasonably well documented, right?
Well... not quite. I managed to get it to run... but not well.
