Immich (photos) + Jellyfin (movies/TV) + Tailscale (access from anywhere). Commands only, in the order they're run in the video.
Tested August 2026 on:
| Hardware | Raspberry Pi 5, 8GB — CanaKit Starter Kit PRO |
| CLSID,ClassName | |
| {0000031A-0000-0000-C000-000000000046},CLSID | |
| {0000002F-0000-0000-C000-000000000046},CLSID CLSID_RecordInfo | |
| {00000100-0000-0010-8000-00AA006D2EA4},CLSID DAO.DBEngine.36 | |
| {00000101-0000-0010-8000-00AA006D2EA4},CLSID DAO.PrivateDBEngine.36 | |
| {00000103-0000-0010-8000-00AA006D2EA4},CLSID DAO.TableDef.36 | |
| {00000104-0000-0010-8000-00AA006D2EA4},CLSID DAO.Field.36 | |
| {00000105-0000-0010-8000-00AA006D2EA4},CLSID DAO.Index.36 | |
| {00000106-0000-0010-8000-00AA006D2EA4},CLSID DAO.Group.36 | |
| {00000107-0000-0010-8000-00AA006D2EA4},CLSID DAO.User.36 |
| sudo apt-get install fcitx im-config | |
| im-config ## choose fcitx | |
| sudo apt-get install fcitx-googlepinyin | |
| ## choose fcitx keyboard icon, choose "Text Entry Setting" | |
| ## in the opned windows, click "+" icon | |
| ## search "pinyin" and Google Pinin" will come out | |
| ## if cannot not be used immediately, log out once |
| %UserProfile% | explorer "shell:::{59031a47-3f72-44a7-89c5-5595fe6b30ee}" | |
|---|---|---|
| %UserProfile%\Desktop | explorer "shell:::{B4BFCC3A-DB2C-424C-B029-7FE99A87C641}" | |
| %UserProfile%\Documents | explorer "shell:::{A8CDFF1C-4878-43be-B5FD-F8091C1C60D0}" | |
| %UserProfile%\Downloads | explorer "shell:::{088e3905-0323-4b02-9826-5d99428e115f}" | |
| %UserProfile%\Pictures | explorer "shell:::{24ad3ad4-a569-4530-98e1-ab02f9417aa8}" | |
| Add Network Location | explorer "shell:::{D4480A50-BA28-11d1-8E75-00C04FA31A86}" | |
| Additional Information | explorer "shell:::{C58C4893-3BE0-4B45-ABB5-A63E4B8C8651}\resultPage" | |
| Advanced Problem Reporting Settings | explorer "shell:::{BB64F8A7-BEE7-4E1A-AB8D-7D8273F7FDB6}\pageAdvSettings" | |
| Advanced sharing settings | explorer "shell:::{8E908FC9-BECC-40f6-915B-F4CA0E70D03D}\Advanced" |
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.
This pamphlet is addressed at folks who know Lojban. They've read not just a tutorial like la karda, the Crash Course, or the Wave Lessons, but also CLL and the BPFK Sections, and some of the various notes from many community members.
I am not aiming to teach the syntax of Lojban, but to radically and fundamentally approach the logical foundations of the semantics of Lojban. We will not start with pronouns, but with relations, and we will always keep the mathematics in mind as we progress.
A common theme in the Lojban community is an uncertainty about what words mean. Since words are treacherous and don't have ultimate meaning, and many Lojbanists are philosophers, it is predictably common for such uncer
This OAuth client is used solely by its owner for personal rclone backups of their own Google Drive. No third-party data is collected, stored, or shared.
Before we look at some common commands, I just want to note a few keyboard commands that are very helpful:
Up Arrow: Will show your last commandDown Arrow: Will show your next commandTab: Will auto-complete your commandCtrl + L: Will clear the screen