Search

method: "POST",

body: JSON.stringify({

"url": "https://en.wikipedia.org/wiki/OpenAI",

"elements": [{

// The second <p> element on the page

* It uses OpenAI API to generate detailed and concise prompts.

const { OpenAI } = await import("https://esm.town/v/std/openai");

const openai = new OpenAI();

console.log("Sending request to OpenAI:", JSON.stringify(analysisMessages, null, 2));

const completion = await openai.chat.completions.create({

console.log("Received response from OpenAI:", JSON.stringify(completion, null, 2));

const { OpenAI } = await import("https://esm.town/v/std/openai");

const openai = new OpenAI();

console.log("Sending clarification request to OpenAI:", JSON.stringify(analysisMessages, null, 2));

const completion = await openai.chat.completions.create({

import { OpenAI } from "https://esm.town/v/std/openai";

import { fetchJSON } from "https://esm.town/v/stevekrouse/fetchJSON?v=41";

const openai = new OpenAI();

const ok = new Response(undefined, { status: 200 });

async function ahoy(prompt: string): Promise<string> {

const completion = await openai.chat.completions.create({

messages: [

const characterModel = new ModelProvider({

id: `${characterName}`,

// for web search / tool use, use openai

provider: 'openai',

model: 'gpt-4o',

// provider: 'groq',

const fileResponses = await Promise.all(chunks.map((chunk, index) => createGzipFile(chunk, index, gzip, introspect)));

console.log(`Created ${fileResponses.length} ${gzip ? "gzip" : ""} files`);

return new Response(JSON.stringify({ openaiFileResponse: fileResponses }), {

status: 200,

headers: { "Content-Type": "application/json" },

if (request.url.endsWith("/new-game")) {

const { OpenAI } = await import("https://esm.town/v/std/openai");

const openai = new OpenAI();

const correctMovie = movies[Math.floor(Math.random() * movies.length)];

`Give a rhyming vague description of the movie "${correctMovie}" without mentioning any character names, actor names, or the movie title. The description should be 4 to 8 lines long.`;

const completion = await openai.chat.completions.create({

messages: [{ role: "user", content: prompt }],

import { createRoot } from "https://esm.sh/react-dom/client";

import OpenAI from "https://esm.sh/openai";

const base64Image = reader.result.split(',')[1];

const openai = new OpenAI({

apiKey: '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',

try {

const response = await openai.chat.completions.create({

model: "gpt-4o",

if (url.searchParams.has("paragraphs")) {

const { OpenAI } = await import("https://esm.town/v/std/openai");

const openai = new OpenAI();

const completion = await openai.chat.completions.create({

messages: [

"worrydream", // Bret Victor (dynamicland)

"stevewoz", // Steve Wozniak (apple)

"sama", // Sam Altman (openai, yc)

"geoff", // Geoff Ralston (yc)

"dang", // Dan G (hn)

const webpageText = await webpageResponse.text();

// Use OpenAI as Claude proxy

const { OpenAI } = await import("https://esm.town/v/std/openai");

const openai = new OpenAI();

const completion = await openai.chat.completions.create({

messages: [

Code Commenter is a web application that automatically adds concise and useful comments to your code using OpenAI's language model. It supports JavaScript, TypeScript, and C# languages.

3. When the "Add Comments" button is clicked, the code is sent to the server

4. The server uses OpenAI's API to generate comments for the code

5. The commented code is returned and displayed in the right panel with syntax highlighting

- Val Town: Hosting platform

- OpenAI API: For generating code comments

- The maximum length of code that can be processed is limited by the OpenAI API's token limit

- The quality of comments may vary depending on the complexity of the code and the AI model's capabilities

Please note that the code you submit is sent to OpenAI's servers for processing. Do not submit sensitive or proprietary code that you don't want to be processed by a third-party service.

if (request.method === "POST" && new URL(request.url).pathname === "/comment") {

const { OpenAI } = await import("https://esm.town/v/std/openai");

const openai = new OpenAI();

const { code, language } = await request.json();

const completion = await openai.chat.completions.create({

messages: [

import { extractValInfo } from "https://esm.town/v/pomdtr/extractValInfo?v=29";

import { OpenAI } from "https://esm.town/v/std/openai?v=4";

import { ResultSet, sqlite } from "https://esm.town/v/std/sqlite?v=6";

app.post("/remix/:id", async (c) => {

const openai = new OpenAI();

const { prompt } = await c.req.json();

if (svg === undefined) return c.text("Not found", 404);

const stream = await openai.chat.completions.create({

messages: [

import _ from "npm:lodash@4";

import OpenAI from "npm:openai";

import { renderToString } from "npm:react-dom/server";

const contextWindow: any = await valleGetValsContextWindow(model);

const openai = new OpenAI();

const stream = await openai.chat.completions.create({

model,

import _ from "npm:lodash@4";

import OpenAI from "npm:openai";

import { renderToString } from "npm:react-dom/server";

const contextWindow: any = await valleGetValsContextWindow(model);

const openai = new OpenAI();

const stream = await openai.chat.completions.create({

model,

import _ from "npm:lodash@4";

import OpenAI from "npm:openai";

import { renderToString } from "npm:react-dom/server";

const contextWindow: any = await valleGetValsContextWindow(model);

const openai = new OpenAI();

const stream = await openai.chat.completions.create({

model,