Manual hotfix for:
(works on my machine, use at your discretion)
| /* | |
| * PlantUML View export as Graph Script (PlantUML-V2G) | |
| * Author: Nicolas Figay 2020 | |
| * Version: 0.1 | |
| * This script creates a .puml file with all elements in the selected views - one file per view | |
| * A simple graph is produced, no nesting produced | |
| */ | |
| console.log("PlantUML View export Script"); | |
| load(__DIR__ + "lib/archimate.js"); |
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.
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.
| // @description A notation-driven dice roller for RPG / gameplay scripts. | |
| // @author mindbound | |
| // @version 0.8.0 | |
| // @tags library, dice, rpg, gameplay | |
| /* | |
| * ============================================================================ | |
| * DICE LIBRARY — LumiScript user library (library-type script) | |
| * ============================================================================ | |
| * |
These resources (articles, books, and videos) are useful when you're starting to learn the language, or when you're learning a specific part of the language. This an opinionated list, no doubt. I've compiled this list from writing and teaching Clojure over the last 10 years.
| async function lazyDefine(callback, condition, maxAttempts = 100, time = 100) { | |
| let attempt = 0; | |
| while (attempt < maxAttempts) { | |
| const result = callback(); | |
| if (condition ? condition(result) : result) return result; | |
| await new Promise(res => setTimeout(res, time)); | |
| attempt++; |
