MarketingPip

/* Modified and created by Jared Van Valkengoed */

import puppeteer from "puppeteer";
import * as cheerio from "cheerio";

async function tokenShoter() {
  const browser = await puppeteer.launch({
    headless: false,
    defaultViewport: null,
  });

MarketingPip

Hey Spencer, I have been playing with AI (lots of these rules are little janky - since I am still training it to get better, tho lots of we could pull from it).

I will tag you in a series of these if these are useful (I would assume so). If you want a limit (since these are way to many to sort through lol)

Let me know and I will provide. (Curious too, maybe we could write a script that AI provides test cases expected for rules generated), and if build tests pass, store the passing rules to a file and manually sort through the ones to keep maybe?

That said, here you go! See below!

ps; these rules will get more accurate, and JSON data shorter upon more training obviously. (this is just a glimpse into things)

MarketingPip

[
    "Ius strictum",
    "Noblesse oblige",
    "O tempora o mores!",
    "Deposit of faith",
    "Colorless green ideas sleep furiously",
    "Disjecta membra",
    "magic word",
    "Bunga bunga",
    "Upper ten thousand",

MarketingPip

Hey Spencer

@spencermountain

Do not want to open an issue nor do I know how to contact you! lol (plus this is just a ton of random stuff but hopefully it will be some benefit to you / the compromise project).

Port duckling over

MarketingPip

$(document).ready(function(){
    ace.config.set('basePath', '../js/lib/ace');

    var editor = ace.edit("editor");

    editor.$blockScrolling = Infinity;
    editor.setTheme("ace/theme/monokai");
    editor.getSession().setMode("ace/mode/html");
    editor.setOptions({
        enableBasicAutocompletion: true,

MarketingPip

async function getWordInfo(words, langCode = 'en') {
  const endpointUrl = 'https://query.wikidata.org/sparql';

  const sparqlQuery = `
    SELECT ?word ?lemma (GROUP_CONCAT(DISTINCT ?category; separator="|\$|") AS ?grammar)
    (GROUP_CONCAT(DISTINCT ?forms; separator="|\$|") AS ?LexIDs)
    (GROUP_CONCAT(DISTINCT ?gloss; separator="|\$|") AS ?Senses)
    (GROUP_CONCAT(DISTINCT ?feat2; separator="|\$|") AS ?Uses)
    (GROUP_CONCAT(DISTINCT ?usagewords; separator="|\$|") AS ?SameMeaning)
    WHERE {

MarketingPip

/**!
 * @license WTF-Link-QIDifier Plugin - is an extension for the wtf_wikipedia library. It enhances the functionality of wtf_wikipedia by adding a custom method to the models.Doc class. Allowing you to enrich Wikipedia document links with corresponding Wikidata QIDs.
 * VERSION: 1.0.0
 * CREATED BY: JARED VAN VALKENGOED
 * DO NOT REMOVE THIS NOTICE
 */

import wtf from "https://esm.sh/wtf_wikipedia";

MarketingPip

package main

import (
	"encoding/json"
	"fmt"
	"io/ioutil"
	"net/http"
	"os"
)

MarketingPip

function callAllFunctions(functionsObj) {
  const resultsArr = [];

  // Loop through each key-value pair in the object
  for (let key in functionsObj) {
    if (typeof functionsObj[key] === 'function') {
      const result = functionsObj[key](); // Call the current function
      resultsArr.push(result); // Add the result to array
    }
  }

MarketingPip

{
    "50 Cent": "PERS",
    "AT&T": "ORG",
    "Abraham Lincoln": "PERS",
    "Acropolis": "LOC",
    "Adam Sandler": "PERS",
    "Adolf Hitler": "PERS",
    "Adriana Lima": "PERS",
    "Afghanistan": "LOC",
    "Africa": "LOC",