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

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

const openai = new OpenAI();

const url = new URL(request.url);

try {

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

model: "gpt-4o",

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 { sleep } from "https://esm.town/v/stevekrouse/sleep?v=1";

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

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

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

import { StreamingTextResponse, streamText } from "npm:ai";

let vercelModel;

if (model.includes("gpt")) {

vercelModel = openai(model);

} else {

vercelModel = anthropic(model);

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

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

import cronstrue from "npm:cronstrue";

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

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 (request.method === 'POST') {

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

const openai = new OpenAI();

try {

const { text } = await request.json();

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

messages: [

export async function ListenTo(req, res) {

const { val = "zzz.demoOpenAIGPT4Summary" } = req.query;

const url = `https://api.val.town/v1/run/${val.replace("@", "")}`

const resp = await fetch(url);

try {

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

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

const openai = new OpenAI();

const body = await request.json();

try {

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

messages: [

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

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

const openai = new OpenAI();

try {

messages.push({ role: "user", content: prompt });

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

messages: messages,

} catch (error) {

console.error("OpenAI API error:", error);

return new Response(

This val creates an email address that posts forwarded emails to a [Campsite](https://campsite.com) channel.

It uses GPT-4 to extract a readable version of the forwarded email from the raw body. If you don't want to use GPT-4, omit the `OPENAI_API_KEY` and the raw body will be included in the post. Other providers are available via [Vercel's AI SDK](https://sdk.vercel.ai/docs/introduction#model-providers).

For help with creating integrations, check out the [Campsite API docs](https://app.campsite.com/campsite/p/notes/campsite-api-docs-l07d7gm5n5rm). You'll need to create an integration and get an API key.

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

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

import { generateObject } from "npm:ai";

const OPENAI_API_KEY = Deno.env.get("OPENAI_API_KEY");

const campsite = new Campsite({ apiKey: CAMPSITE_API_KEY });

let subject = payload.subject || "Forwarded email (no subject)";

if (OPENAI_API_KEY) {

const openai = createOpenAI({ apiKey: OPENAI_API_KEY });

// Extract name and email from the forwarded message

const { object: { name, email, subject, message } } = await generateObject({

model: openai("gpt-4-turbo"),

schema: z.object({

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: [

- [[https://www.val.town/v/stevekrouse/valwriter]]

- _Note_: It looks like openai enhancement was dropped at some point when adding all the gizmos;

<path stroke-linecap="round" stroke-linejoin="round" d="M20.25 8.511c.884.284 1.5 1.128 1.5 2.097v4.286c0 1.136-.847 2.1-1.98 2.193-.34.027-.68.052-1.02.072v3.091l-3-3c-1.354 0-2.694-.055-4.02-.163a2.115 2.115 0 0 1-.825-.242m9.345-8.334a2.126 2.126 0 0 0-.476-.095 48.64 48.64 0 0 0-8.048 0c-1.131.094-1.976 1.057-1.976 2.192v4.286c0 .837.46 1.58 1.155 1.951m9.345-8.334V6.637c0-1.621-1.152-3.026-2.76-3.235A48.455 48.455 0 0 0 11.25 3c-2.115 0-4.198.137-6.24.402-1.608.209-2.76 1.614-2.76 3.235v6.226c0 1.621 1.152 3.026 2.76 3.235.577.075 1.157.14 1.74.194V21l4.155-4.155"></path>

</svg>

<div class="font-semibold group-hover:text-black">OpenAI chat completion</div>

</button>

<button class="group bg-gray-50 border-gray-300 flex items-center gap-2 overflow-hidden rounded border p-3 text-left transition-colors hover:border-blue-500 hover:shadow-md">

&& new URL(request.url).pathname === "/generate-blog"

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

const openai = new OpenAI();

try {

if (topic === "RANDOM") {

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

messages: [

topicPrompt = `Write a brief blog post about ${topic}. Keep it concise and engaging, around 200-300 words.`;

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

messages: [

headers: { 'Content-Type': 'application/json' }

// Generate new emoji using OpenAI

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

const openai = new OpenAI();

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

messages: [{ role: "user", content: `Generate a single emoji that best represents "${name}". Respond with only the emoji, nothing else.` }],