1// This approach will fetch data from the specified endpoint, process it to create a GitHub-style contribution chart,
2// and render it using React. We'll use the fetch API to get the data, process it to create a heatmap-like structure,
3// and then use CSS Grid to render the chart with varying shades of green based on the number of vals created each day.
4
5/** @jsxImportSource https://esm.sh/react */
6import React, { useState, useEffect } from "https://esm.sh/react";
7import { createRoot } from "https://esm.sh/react-dom/client";
8
9function App() {
4 * and enables exploration of related topics or deeper dives using arrow keys or buttons.
5 */
6/** @jsxImportSource https://esm.sh/react@18.2.0 */
7import React, { useState, useEffect, useCallback } from "https://esm.sh/react@18.2.0";
8import { createRoot } from "https://esm.sh/react-dom@18.2.0/client";
9
10const SUGGESTIONS = ["Quantum Computing", "Renaissance Art", "Climate Change", "Artificial Intelligence", "Space Exploration"];
8 */
9
10/** @jsxImportSource https://esm.sh/react */
11import React, { useEffect, useState } from "https://esm.sh/react";
12import { createRoot } from "https://esm.sh/react-dom/client";
13
14function App() {
3// TailwindCSS is used for styling.
4
5/** @jsxImportSource https://esm.sh/react */
6import React, { useState, useEffect, useRef } from "https://esm.sh/react";
7import { createRoot } from "https://esm.sh/react-dom/client";
8
9function App() {
1/** @jsxImportSource npm:preact */
2import { render } from "npm:preact-render-to-string";
3
4/**
1/** @jsxImportSource https://esm.sh/react */
2import React, { useState } from "https://esm.sh/react";
3import { createRoot } from "https://esm.sh/react-dom/client";
4
5function App() {
1/** @jsxImportSource https://esm.sh/react */
2import { renderToString } from "npm:react-dom/server";
3
4export default async function(req: Request) {
1/**
2 * This code creates a search engine prototype with autocomplete functionality using the Cerebras LLM API.
3 * It uses React for the frontend and the Cerebras API for generating autocomplete suggestions.
4 * The suggestions are cached in the browser to reduce API calls.
5 * It implements a two-step LLM process: first to get initial suggestions, then to filter them for sensibility and ethics.
7 */
8
9/** @jsxImportSource https://esm.sh/react */
10import debounce from "https://esm.sh/lodash.debounce";
11import React, { useEffect, useRef, useState } from "https://esm.sh/react";
12import { createRoot } from "https://esm.sh/react-dom/client";
13
14function App() {
1/**
2 * This code creates a geocoder widget similar to the Google Maps API search widget.
3 * It uses React for the frontend, the Cerebras API for LLM-based geocoding,
4 * and Leaflet for displaying the map.
5 */
6
7/** @jsxImportSource https://esm.sh/react */
8import React, { useState, useEffect, useRef } from "https://esm.sh/react";
9import { createRoot } from "https://esm.sh/react-dom/client";
10import debounce from "https://esm.sh/lodash.debounce";
11
2// It provides a form for users to input the image URL and size, and displays the resized image.
3
4/** @jsxImportSource https://esm.sh/react */
5import React, { useState } from "https://esm.sh/react";
6import { createRoot } from "https://esm.sh/react-dom/client";
7
8function App() {
11 const [resizedImageUrl, setResizedImageUrl] = useState("");
12
13 const handleSubmit = async (e: React.FormEvent) => {
14 e.preventDefault();
15 const response = await fetch(`?link=${encodeURIComponent(imageUrl)}&size=${size}`);
