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- @pomdtr/ask_ai

* and activity (befriends aliens, goes to the doctor, rides a rollercoaster, bakes a cake for friends)

It uses OpenAI to write a children's bedtime story

* title

for a "fantastical story about a green whale who rides the bus" or the "spooky story about the tomato fox who explores a cave".

Then using the summary, OpenAI geenrates another prompt to describe the instructions to generate a children's story book image.

That's sent to Fal to generate an image.

import { ValTownLink } from "https://esm.town/v/dthyresson/viewOnValTownComponent";

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

import * as fal from "npm:@fal-ai/serverless-client";

{ name: "Fly.io", icon: "🪰" },

{ name: "Val.town", icon: "🏘️" },

{ name: "OpenAI", icon: "🧠" },

{ name: "SQLite", icon: "🗃️" },

{ name: "Commander", icon: "🎖️" },

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,

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:

Add OpenAI key to Val Town

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.

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,

* 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,

// Configuration

const API_CONFIG = {

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

method: "POST",

mode: "cors",

import Jimp from "npm:jimp";

import OpenAI from "npm:openai";

import { z } from "npm:zod";

const HABITIFY_API_KEY = process.env.HABITIFY_API_KEY;

const OPENAI_API_KEY = process.env.OPENAI_API_KEY;

const DEF_TIMEZONE = "America/Los_Angeles"; // Get your timezone from here: https://stackoverflow.com/a/54500197

const todoistapi = new TodoistApi(TODOIST_API_KEY);

const oai = new OpenAI({

apiKey: OPENAI_API_KEY ?? undefined,

const client = Instructor({

const tabooResponse = await fetchOpenAIText(tabooPrompt);

return fetchOpenAIStream(cluePrompt);

async function fetchOpenAIText(content: string): string {

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

const openai = new OpenAI();

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

export async function fetchOpenAIStream(content: string): Promise<Response> {

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

const openai = new OpenAI();

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

* HTML (probably overcomplicates things; should remove)

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

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

import cronstrue from "npm:cronstrue";

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