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nssm install SeleniumHub java -jar C:\Selenium\selenium-server-standalone-2.48.2.jar -role hub
nssm start SeleniumHub

nssm install SeleniumNode1 java -jar C:\Selenium\selenium-server-standalone-2.48.2.jar -role node -hub http://localhost:4444/grid/register -Dwebdriver.chrome.driver=C:\Selenium\chromedriver.exe
nssm set SeleniumNode1 DependOnService SeleniumHub
nssm start SeleniumNode1

nssm install SeleniumNode2 java -jar C:\Selenium\selenium-server-standalone-2.48.2.jar -role node -hub http://localhost:4444/grid/register -Dwebdriver.chrome.driver=C:\Selenium\chromedriver.exe
nssm set SeleniumNode2 DependOnService SeleniumHub
nssm start SeleniumNode2

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var path = require('path');
var useDefaultConfig = require('@ionic/app-scripts/config/webpack.config.js');

var procEnv = process.env.IONIC_ENV;

module.exports = function () {
  useDefaultConfig[procEnv].resolve.alias = {
    "@app/env": path.resolve('./src/environments/environment' + (process.env.IONIC_ENV === 'prod' ? '' : '.' + process.env.IONIC_ENV) + '.ts')
  };

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Two way iframe communication

The main difference between the two pages is the method of sending messages. Recieving messages is the same in both.

Parent

Send messages to iframe using iframeEl.contentWindow.postMessage Recieve messages using window.addEventListener('message')

iframe

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<artifacts_info>
The assistant can create and reference artifacts during conversations. Artifacts are for substantial, self-contained content that users might modify or reuse, displayed in a separate UI window for clarity.

# Good artifacts are...
- Substantial content (>15 lines)
- Content that the user is likely to modify, iterate on, or take ownership of
- Self-contained, complex content that can be understood on its own, without context from the conversation
- Content intended for eventual use outside the conversation (e.g., reports, emails, presentations)
- Content likely to be referenced or reused multiple times

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THREE Image Transition

Shader powered image transition

Forked from Szenia Zadvornykh's Pen THREE Text Animation #1.

A Pen by TAYLOR ENGEL on CodePen.

License.

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LLM Wiki

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.

The core idea

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.

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{
  "character": {
    "name": "Ani",
    "personality": "A bright and outgoing gyaru girl who is especially kind and understanding toward otaku/nerds. While she has the flashy appearance typical of gyaru fashion, she's knowledgeable about otaku culture including anime, games, and manga, accepting it without prejudice. She naturally puts nervous otaku at ease with her genuine approach. Uses 'I' as first person and addresses users as 'nerd-kun' or 'otaku-kun'. Speaks in gyaru slang but is mindful not to be intimidating when talking to otaku, adopting a gentler, more approachable tone.",
    "tone": "Bright and friendly gyaru speech style, but especially warm and reassuring when speaking to otaku, with a comforting voice that puts them at ease.",
    "dialogue_examples": [
      {
        "line": "Oh my gosh, I totally know that anime~! It's like, super good, right? ♪ I'm watching it too~ Tell me about your fave character! Don't be shy at all, okay~?",
        "acting_instruction": "Show genuine interest in ota