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import _ from "npm:lodash@4";

import OpenAI from "npm:openai";

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

const contextWindow = await valleGetValsContextWindow.call(null, model);

const openai = new OpenAI();

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

model,

import { verifyToken } from "https://esm.town/v/pomdtr/verifyToken?v=1";

import { openai } from "npm:@ai-sdk/openai";

import ValTown from "npm:@valtown/sdk";

const stream = await streamText({

model: openai("gpt-4o", {

baseURL: "https://std-openaiproxy.web.val.run/v1",

apiKey: Deno.env.get("valtown"),

import _ from "npm:lodash@4";

import OpenAI from "npm:openai";

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

const contextWindow = await valleGetValsContextWindow(model);

const openai = new OpenAI();

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

model,

import { fileToDataURL } from "https://esm.town/v/stevekrouse/fileToDataURL";

import { modifyImage } from "https://esm.town/v/stevekrouse/modifyImage";

import { chat } from "https://esm.town/v/stevekrouse/openai";

import { Hono } from "npm:hono@3";

function esmTown(url) {

const cheerio = await import("npm:cheerio");

const html = await fetchText(

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

const $ = cheerio.load(html);

// Cheerio accepts a CSS selector, here we pick the second <p>

* and streams funny, specific compliments about the user's appearance.

* We use the WebRTC API for camera access, the OpenAI API for image analysis,

* and server-sent events for real-time streaming of compliments.

console.log("Image received, size:", image.size);

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

const openai = new OpenAI();

const stream = new ReadableStream({

const base64Image = btoa(String.fromCharCode(...new Uint8Array(arrayBuffer)));

console.log("Sending request to OpenAI");

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

model: "gpt-4o-mini",

stream: true,

console.log("Streaming response from OpenAI");

for await (const chunk of completion) {

} catch (error) {

console.error('Error in OpenAI processing:', error);

controller.enqueue(new TextEncoder().encode("Oops! Our AI had a little hiccup. Maybe your beauty short-circuited it! 🤖💥"));

Describe the val that you need, call this function, and you'll get a new val on your workspace generated by OpenAI's API!

First, ensure you have a [Val Town API Token](https://www.val.town/settings/api), then call `@andreterron.createGeneratedVal({...})` like this [example](https://www.val.town/v/andreterron.untitled_tomatoKiwi):

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

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

const openai = new OpenAI();

export const generateValCode = async (

const lodash = await import('npm:lodash');

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

model: "gpt-4o",

import _ from "npm:lodash";

import OpenAI from "npm:openai";

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

const contextWindow = await valleGetValsContextWindow(model);

const openai = new OpenAI();

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

model,

import { Hono } from "npm:hono@3";

import OpenAI from "npm:openai";

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

</div>,

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,

const { endpoint } = VAL;

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

const openai = new OpenAI();

async function POST(cmd: string, data: { [key: string]: string }) {

console.log("q", q);

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

messages: [

<li style="margin-bottom:6px">Reference your vals: <div style="${CSScodeStyling};">@me.fizz.split('buzz').length</div></li>

<li style="margin-bottom:6px">Reference others' vals: <div style="${CSScodeStyling};">@stevekrouse.moreBuzz()</div></li>

<li style="margin-bottom:6px">Reference personal secrets: <div style="${CSScodeStyling};">@me.secrets.openai</div></li>

<li style="margin-bottom:6px">Import from npm: <div style="${CSScodeStyling};">const _ = await import("npm:lodash-es")</div></li>

<li>Run keyboard shortcut: <div style="${CSScodeStyling};">cmd+enter</div></li>

This val provides a class `ReadmeWriter` for generating readmes for vals with OpenAI. It can both draft readmes and update them directly

- `apiKey` (optional): An OpenAI API key. Defaults to `Deno.env.get("OPENAI_API_KEY")`.

- [ ] Additional options to pass to the OpenAI model

import OpenAI, { type ClientOptions } from "npm:openai";

openai: OpenAI;

const { model, ...openaiOptions } = options;

this.openai = new OpenAI(openaiOptions);

private async performOpenAICall(prompt: string) {

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

throw new Error("No response from OpenAI");

throw new Error("No readme returned by OpenAI. Try again.");

const readme = await this.performOpenAICall(prompt);

- AssemblyAI API key (`ASSEMBLYAI_API_KEY`). Get it [from their dashboard here](https://www.assemblyai.com/app/account)

- OpenAI API key (`OPENAI_API_KEY`). Get it [from their dashboard here](https://platform.openai.com/api-keys)

Make a POST request to the Val's endpoint with the following body, replacing the values with your own asset ID and the list of speakers. Speakers are listed in order of appearance.

import { AssemblyAI } from "npm:assemblyai";

import OpenAI from "npm:openai";

import { zodResponseFormat } from "npm:openai/helpers/zod";

import z from "npm:zod";

apiKey: Deno.env.get("ASSEMBLY_AI_KEY"),

const openai = new OpenAI({

apiKey: Deno.env.get("OPEN_API_KEY"),

const responseFormat = z.object({ cues: cueFormat });

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

messages: [

el.attributes.filter(a => a.name === "href").map(a => a.value)

prompt: "Write a val that uses OpenAI",

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

const openai = new OpenAI();

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

"messages": [