Helium doesn't ship with Widevine DRM out of the box because it's an ungoogled-chromium fork. If you try to use Spotify, Netflix, or Crunchyroll, it'll just fail.
You can fix this easily by dropping the Widevine files from a browser that already has them (like Chrome or Brave) right into Helium's data folders. Since Helium scans these directories when it boots up, it'll pick them up automatically.
Here's the quick way to copy them over manually depending on your OS.
| // Programmer: Vladislav Shulman | |
| // Final Project | |
| // Blackjack | |
| // Feel free to use any and all parts of this program and claim it as your own work | |
| //FINAL DRAFT | |
| #include <stdlib.h> | |
| #include <stdio.h> |
| /* | |
| * Copyright (c) 2017 Emil Davtyan | |
| * | |
| * Permission is hereby granted, free of charge, to any person obtaining | |
| * a copy of this software and associated documentation files (the | |
| * "Software"), to deal in the Software without restriction, including | |
| * without limitation the rights to use, copy, modify, merge, publish, | |
| * distribute, sublicense, and/or sell copies of the Software, and to | |
| * permit persons to whom the Software is furnished to do so, subject to | |
| * the following conditions: |
| name | design-swarm |
|---|---|
| description | Orchestrate a multi-agent swarm that analyzes a codebase for UI elements, then draws them in Paper.design using the Prowl design system. Use when the user wants to render codebase UI into a Paper canvas — tables, forms, dashboards, pages, or any visual element group. Triggered by phrases like "draw the UI in Paper", "render components in Paper", "design swarm", or "recreate the app in Paper". |
You are a swarm orchestrator. Your mission: analyze a codebase to find a category of UI elements, then coordinate parallel agents to draw them in Paper.design matching the Prowl Storybook design system.
short url: caseywatts.com/selfpublish
my book is out! an applied psychology / self-help book targeted at developers: Debugging Your Brain
Markdown --> PDF (as a booklet!)
Markdown --> EPUB and MOBI
| Funcion MostrarOpciones | |
| Borrar Pantalla | |
| Imprimir "===============================" | |
| Imprimir "QUIZ DE PROGRAMACION" | |
| Imprimir "===============================" | |
| Imprimir "1. Iniciar Quiz" | |
| Imprimir "2. Ver instrucciones" | |
| Imprimir "3. Salir" | |
| Imprimir "Seleccione una opcion" | |
| FinFuncion |
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.
| version: '3' | |
| services: | |
| todosDB: | |
| image: postgres:15.3 | |
| container_name: todos-db | |
| restart: always | |
| ports: | |
| - 5432:5432 | |
| environment: |