Search

browserWSEndpoint: `wss://chrome.browserless.io?token=${process.env.browserlessKey}`,

const page = await browser.newPage();

await page.goto("https://en.wikipedia.org/wiki/OpenAI");

const intro = await page.evaluate(

`document.querySelector('p:nth-of-type(2)').innerText`,

export let generateValCodeAPI = (description: string) =>

generateValCode(

process.env.VT_OPENAI_KEY,

description,

export const textToImageDalle = async (

openAIToken: string,

prompt: string,

} = await fetchJSON(

"https://api.openai.com/v1/images/generations",

method: "POST",

"Content-Type": "application/json",

"Authorization": `Bearer ${openAIToken}`,

body: JSON.stringify({

export const getJoke = (async () => {

const { ChatCompletion } = await import("npm:openai");

const result = await ChatCompletion.create({

model: "gpt-3.5-turbo",

import { html } from "https://esm.sh/hono/html";

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

const app = new Hono();

app.get("/market-data", async (c) => {

const openai = new OpenAI();

try {

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

model: "gpt-4o-mini",

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

const openai = new OpenAI();

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

model: "gpt-4o-mini",

import { email } from "https://esm.town/v/std/email?v=11";

import { OpenAI } from "npm:openai";

let location = "munchen";

).then(r => r.json());

const openai = new OpenAI();

let chatCompletion = await openai.chat.completions.create({

messages: [{

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

async function summarizePage(input, isUrl = true) {

text = input;

// Initialize OpenAI API using your own API key

const openai = new OpenAI({

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

// Use OpenAI API to summarize the text

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

messages: [{

"Access-Control-Allow-Methods": "GET, POST, OPTIONS",

"Access-Control-Allow-Headers": "Content-Type, X-OpenAI-Key",

"Access-Control-Max-Age": "86400",

return new Response(null, { headers, status: 204 });

const apiKey = req.headers.get("X-OpenAI-Key");

if (!apiKey) {

browserWSEndpoint: `wss://chrome.browserless.io?token=${process.env.browserlessKey}`,

const page = await browser.newPage();

await page.goto("https://en.wikipedia.org/wiki/OpenAI");

const intro = await page.evaluate(

`document.querySelector('p:nth-of-type(2)').innerText`,

* Make a folder for the temporary vals that get generated, take the ID from the URL, and put it in `tempValsParentFolderId`.

* If you want to use OpenAI models you need to set the `OPENAI_API_KEY` [env var](https://www.val.town/settings/environment-variables).

* If you want to use Anthropic models you need to set the `ANTHROPIC_API_KEY` [env var](https://www.val.town/settings/environment-variables).

options = {},

// Initialize OpenAI API stub

const { Configuration, OpenAIApi } = await import("https://esm.sh/openai");

const configuration = new Configuration({

apiKey: process.env.openAIAPI,

const openai = new OpenAIApi(configuration);

// Request chat completion

: prompt;

const { data } = await openai.createChatCompletion({

model: "gpt-3.5-turbo-0613",

export default async function server(request: Request): Promise<Response> {

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

const { sqlite } = await import("https://esm.town/v/stevekrouse/sqlite");

const openai = new OpenAI();

const SCHEMA_VERSION = 2;

// Generate AI response

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

messages: [

if (request.method === "POST") {

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

const openai = new OpenAI();

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

cpp: "Generate a clean, concise C++ code snippet for: "

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

messages: [

import { email } from "https://esm.town/v/std/email?v=11";

import { OpenAI } from "npm:openai";

let location = "toronto on";

).then(r => r.json());

const openai = new OpenAI();

let chatCompletion = await openai.chat.completions.create({

messages: [{

Uses [Turso](https://turso.tech/) to search embeddings of all vals, using the [sqlite-vss](https://github.com/asg017/sqlite-vss) extension.

- Call OpenAI to generate an embedding for the search query.

- Query the `vss_vals_embeddings` table in Turso using `vss_search`.

import { db as allValsDb } from "https://esm.town/v/sqlite/db?v=9";

import OpenAI from "npm:openai";

export default async function semanticSearchPublicVals(query) {

authToken: Deno.env.get("TURSO_AUTH_TOKEN_VALSEMBEDDINGS"),

const openai = new OpenAI();

const embedding = await openai.embeddings.create({

model: "text-embedding-3-small",

"Rewrite this fact about cats as if it was written for 3 year old:\n\n" +

fact;

const story = await fetch("https://api.openai.com/v1/chat/completions", {

method: "POST",

body: JSON.stringify({

temperature: 0.7,

headers: {

"Authorization": `Bearer ${process.env.OPENAI}`,

"Content-Type": "application/json",

}).then(async (response) => {