hubgit

[50, 100, 3].toSorted(Intl.Collator('en', { numeric: true }).compare)

hubgit

import RSSParser from 'npm:rss-parser'

await Deno.mkdir('audio', { recursive: true })

const feedURL = 'https://anchor.fm/s/1252b450/podcast/rss'
const feed = await new RSSParser().parseURL(feedURL)

for (const item of feed.items) {
  const { url } = item.enclosure
  console.log(url)

hubgit

const links = document.querySelectorAll('a[download]')

if (links.length === 0) {
    console.log("No downloadable files found")
    return
}

const handle = await showSaveFilePicker({ 
    suggestedName: 'files.zip', 
    types: [{ 

hubgit

brew install git-lfs 

git clone https://github.com/ml-explore/mlx-examples
cd mlx-examples/llms/mixtral
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1
cd Mixtral-8x7B-Instruct-v0.1
git lfs pull --include "consolidated.*.pt" # ~100GB
git lfs pull --include "tokenizer.model"

hubgit

import { DOMParser, type Element, } from "https://deno.land/x/deno_dom@v0.1.43/deno-dom-wasm.ts";

const parser = new DOMParser()

const fetchDOM = async (url: string) => {
  const response = await fetch(url)
  if (!response.ok) {
    throw new Error('Response was not ok')
  }
  const html = await response.text()

hubgit

import type { NextRequest } from 'next/server'
import { createParser } from 'eventsource-parser'

export const config = {
  runtime: 'edge',
}

export default async function handler(req: NextRequest) {
  const encoder = new TextEncoder()
  const decoder = new TextDecoder()

hubgit

# brew install awscli
# aws configure
aws s3 cp your-file.pdf s3://your-bucket/your-file.pdf

# https://pypi.org/project/amazon-textract-helper/
# https://github.com/aws-samples/amazon-textract-textractor/tree/master/helper
# pip install amazon-textract-helper
amazon-textract --input-document s3://your-bucket/your-file.pdf --features TABLES --pretty-print TABLES --pretty-print-table-format=csv

# https://aws.amazon.com/blogs/machine-learning/automatically-extract-text-and-structured-data-from-documents-with-amazon-textract/

hubgit

[...document.querySelectorAll('div,main,body')].forEach(node => {
    node.style.position = 'relative'
    node.style.height = 'auto'
    node.style.overflowY = 'visible'
});

[...document.querySelectorAll('button')].forEach(node => {
    node.remove()
});

hubgit

get_iplayer --pid m001d2h4 --subtitles --output "m001d2h4"        
ffmpeg -i m001d2h4/Only_Connect_Series_18_-_07._Scrummagers_v_Crustaceans_m001d2h4_original.mp4 -vf "subtitles=m001d2h4/Only_Connect_Series_18_-_07._Scrummagers_v_Crustaceans_m001d2h4_original.srt" -ss 17:49 -t 5 -copyts output.mov

hubgit

lineReader = () => {
  let buffer = "";

  return new TransformStream({
    transform(chunk, controller) {
      buffer += chunk;
      const parts = buffer.split("\n");
      parts.slice(0, -1).forEach((part) => controller.enqueue(part));
      buffer = parts[parts.length - 1];
    },