Scripts by johnlindquist

import '@johnlindquist/kit'
import Jimp from 'jimp'

let downloadsPath = home('Downloads')
let files = await readdir(downloadsPath)
let pngFiles = files.filter(file => file.toLowerCase().endsWith('.png'))

let filesWithStats = []
for (let pngFile of pngFiles) {
  let filePath = path.join(downloadsPath, pngFile)
  let stats = await stat(filePath)
  filesWithStats.push({ path: filePath, stats })
}

filesWithStats.sort((a, b) => b.stats.mtimeMs - a.stats.mtimeMs)

let latestTwoImages = filesWithStats.slice(0, 2)

if (latestTwoImages.length < 2) {
  await div(md(`## Not enough PNG images found in Downloads`))
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// Name: Barbarian Chat
// Description: Chat with an AI Barbarian
// Author: Bard

import '@johnlindquist/kit'import { ChatOpenAI } from '@langchain/openai'
import { ChatPromptTemplate, MessagesPlaceholder } from '@langchain/core/prompts'
import { START, END, MessagesAnnotation, StateGraph, MemorySaver } from '@langchain/langgraph'
import { trimMessages } from '@langchain/core/messages'

let id: NodeJS.Timeout | number = -1;
let currentMessage: string = ``;

const llm = new ChatOpenAI({
  modelName: 'gpt-4o-mini',
  apiKey: await env('OPENAI_API_KEY'),
  temperature: 0.7,
  streaming: true,
  callbacks: [
    {
      handleLLMStart: async () => {
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// Author: johnlindquist

// Name: Batch Image Renamer
// Description: Rename images in a directory with Faker-generated names
// Author: johnlindquist

import '@johnlindquist/kit'
import { faker } from '@faker-js/faker'

// Prompt user to select a directory containing images
const imageDir = await path({
  onlyDirs: true,
  placeholder: 'Select a directory with images to rename',
})

// Read files from the selected directory
const imageFiles = await readdir(imageDir)
  .then(files => files.filter(file => /\.(jpe?g|png|gif)$/i.test(file))) // Filter for common image types
  .catch(error => {
    console.error('Error reading directory:', error)
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// Name: File Organizer
// Description: Automatically organize files by type or date
// Author: johnlindquist

import '@johnlindquist/kit'
import path from 'node:path'

/**
 * Interface for file information.
 */
interface FileInfo {
  name: string
  path: string
  extension: string
}

/**
 * Extracts file information from a given file path.
 * @param filePath The path to the file.
 * @returns An object containing the file's name, path, and extension.
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// Name: Greet Editor
// Description: Opens editor with greeting
// Author: johnlindquist

import '@johnlindquist/kit'

const name = await arg<string>('Say hello to?');

// Open the editor with a greeting message.
await editor(`Hello, ${name}!`);

// Name: Image to Base64 Markdown
// Description: Convert image URL to Base64 Markdown & copy to clipboard
// Author: johnlindquist

import '@johnlindquist/kit'
import type { AxiosResponse } from 'axios'

/**
 * Converts an image from a URL to Base64 Markdown and copies it to the clipboard.
 */
try {
  // Prompt for the image URL
  const imageUrl: string = await arg('Enter the image URL')

  // Fetch the image data as ArrayBuffer
  const response: AxiosResponse<ArrayBuffer> = await get(imageUrl, { responseType: 'arraybuffer' })

  if (!response.data) {
    throw new Error(`Failed to fetch image from URL: ${imageUrl}`);
  }
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// Name: Showcase
// Description: Demonstrate Script Kit Features
// Author: johnlindquist

import '@johnlindquist/kit'

// 1. Basic input with arg()
const name = await arg<string>("What's your name?")

// 2. Display a welcome message with div() and md()
await div(md(`# Hello, ${name}! Let's explore Script Kit.`))

// 3. Use fields() for structured input
const [favColor, favAnimal] = await fields<[string, string]>([
  "Favorite Color",
  "Favorite Animal",
])

// 4. Show a toast notification
await toast(`You chose ${favColor} and ${favAnimal}!`)
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// Name: Cloudinary Saver
// Description: Saves Reddit posts to Cloudinary
// Author: johnlindquist

import "@johnlindquist/kit"
import cloudinary from 'cloudinary'

// Get Reddit username and Cloudinary credentials from environment variables
const username = await env('REDDIT_USERNAME', {  placeholder: 'Your Reddit username',
})

cloudinary.v2.config({
  cloud_name: await env('CLOUDINARY_CLOUD_NAME'),
  api_key: await env('CLOUDINARY_API_KEY'),
  api_secret: await env('CLOUDINARY_API_SECRET'),
})

/**
 * Fetches saved posts from Reddit for the specified user.
 * @returns {Promise<any[]>} A promise that resolves to an array of Reddit post objects.
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// Name: Prettier Format
// Description: Formats files with Prettier.
// Author: johnlindquist

import '@johnlindquist/kit'import { glob } from 'glob'
import { readFile, writeFile } from 'node:fs/promises'
import { format } from 'prettier'

// Prompt for file patterns and an optional prettier config file
const filePatterns = await fields([
  {
    label: 'File Patterns (comma-separated)',
    placeholder: '*.js, *.ts, *.json',
  },
  {
    label: 'Prettier Config File (optional)',
    placeholder: '.prettierrc.json',
    type: 'text',
  },
])
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// Name: Create Project
// Description: Creates a new project with a chosen framework
// Author: johnlindquist
import "@johnlindquist/kit";const framework = await arg("Choose a framework:", [
  "React",
  "Vue",
  "Svelte",
  "Next.js",
  "Nuxt.js",
]);

const projectName = await arg("Project name:");
const projectDir = path.join(home(), "projects", projectName);

await ensureDir(projectDir);
cd(projectDir);

const createCommand = `npx create-${
  framework.toLowerCase() === "next.js"
    ? "next-app"
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// Name: Log Analyzer
// Description: Analyzes a log file for errors and patterns.
// Author: johnlindquist

import '@johnlindquist/kit';

// Prompt the user to select a log file
const logFile = await path({ placeholder: 'Select a log file' });

// Read the content of the selected log file
const logContent = await readFile(logFile, 'utf-8');

// Define a regular expression to identify error lines (case-insensitive)
const errorRegex = /error|exception|fail/i;

// Filter log lines to find those containing errors
const errorLines = logContent.split('\n').filter(line => errorRegex.test(line));

// Prompt the user to enter a pattern to search for
const pattern = await arg({ placeholder: 'Enter a pattern to search for' });
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// Name: Screenshot Tool
// Description: Capture screen area, save, and share
// Author: johnlindquist
import '@johnlindquist/kit'// Define available screen capture areas
const captureAreas = ["full", "window", "selection"] as const;
type CaptureArea = typeof captureAreas[number];

// Prompt user to select capture area
const area = await arg<CaptureArea>("Select area", captureAreas);

// Prompt user to enter filename, using timestamp as default
const filename = await arg("Enter filename", `${Date.now()}.png`);
const savePath = kenvPath("screenshots", filename);

// Ensure the screenshots directory exists
await ensureDir(kenvPath("screenshots"));

// Execute screen capture command based on selected area
let captureCommand = "";
switch (area) {
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