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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,

if (url.pathname === "/api/summary") {

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

const openai = new OpenAI();

const supabaseUrl = Deno.env.get("SUPABASE_PERSONAL_URL");

title: scrap.title ? scrap.title.substring(0, 256) : "",

// Generate summary using OpenAI

try {

).join("\n");

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

messages: [

redirect: "follow",

let openApiResponse = await fetch(

"https://api.openai.com/v1/chat/completions",

requestOptions,

let jsonResponse = await openApiResponse.json();

A naive approach to this would be a link that looks like this:

<a href="https://www.val.town/settings/environment-variables?name=OpenAI&value=sk-123...">

Add OpenAI key to Val Town

</a>

* HTMX (probably overcomplicates things; should remove)

* @stevekrouse/openai, which is a light wrapper around @std/openai

I'm finding HTMX a bit overpowered for this, so I have two experimental forks without it:

setIsLoading(true);

try {

const response = await fetch("https://esm.town/v/stevekrouse/openai", {

method: "POST",

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

export default function handler(req) {

headers: {

"Content-Type": "text/html",

return { width: availableWidth, height: availableHeight };

const API_CONFIG = {

url: "https://willthereader-openaidefiner.web.val.run",

method: "POST",

mode: "cors",

import { gpt3 } from "https://esm.town/v/patrickjm/gpt3";

import { simpleWeather } from "https://esm.town/v/patrickjm/simpleWeather";

export let weatherTomorrowGpt3 = (params: { openAiKey: string, city: string }) =>

simpleWeather(params.city).then((weather) =>

gpt3({

openAiKey: params.openAiKey,

prompt: `

Given a JSON sequence, give a short, plain-English summary about the weather tomorrow.

try {

// Dynamically import OpenAI to ensure server-side compatibility

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

const openai = new OpenAI();

// Detailed AI prompt for comprehensive analysis

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

model: "gpt-4o",

// Generate narrative description

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

model: "gpt-4o",

* The conversation history is stored as an array of message objects containing sender, content, date, and phone number.

* OpenAI's GPT-4 is used to generate contextual responses based on the conversation history.

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

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

import { Buffer } from "node:buffer";

async function generateAIResponse(history: Message[]): Promise<string> {

const openai = new OpenAI();

const messages: { role: "user" | "assistant" | "system"; content: string }[] = history.map(msg => ({

"You are an AI assistant communicating via SMS. Keep your responses concise and under 160 characters. Your task is to help the user organize their daily work activities and provide brief, helpful responses.",

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

messages,

5. Message @ValTownBot the express endpoint you copied

6. You'll also need an `openai` key in [your secrets](/settings/secrets) for this particular DallE bot to work

try {

let resp = await textToImageDalle(

process.env.openai,

text.replace("/dalle", ""),

1,

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

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

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

console.log(e.from, e.subject);

const openai = new OpenAI();

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

messages: [

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

import { OpenAI } from "npm:openai";

function stripHtmlBackticks(html: string): string {

export default async function(e: Email) {

const openai = new OpenAI();

console.log(`from: ${e.from} to: ${e.to} subject: ${e.subject}, cc: ${e.cc}, bcc: ${e.bcc}`);

from = to;

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

messages: [

new Uint8Array(arrayBuffer).reduce((data, byte) => data + String.fromCharCode(byte), '')

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

const openai = new OpenAI();

try {

const imageAnalysis = await withTimeout(openai.chat.completions.create({

model: "gpt-4o",

? `Previous story summary: ${previousStory[previousStory.length - 1].content}`

const story = await withTimeout(openai.chat.completions.create({

model: "gpt-4o-mini",

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

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

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

console.log(e.from, e.subject);

const openai = new OpenAI();

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

messages: [