Search results for "openai"

valle_tmp_54185991019187464068579562776686

@janpaul123

@jsxImportSource https://esm.sh/react

0

HTTP

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,

valle_tmp_56208884983514818093201845315532

@janpaul123

@jsxImportSource https://esm.sh/react

0

HTTP

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,

valle_tmp_62253074104033147819150473701293

@janpaul123

@jsxImportSource https://esm.sh/react

0

HTTP

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,

awesome

@pomdtr

Awesome Val Town An curated list of useful community vals. Feel free to create your own awesome list! Apps @pomdtr/blob_editor @nbbaier/sqliteExplorerApp View and interact with your Val Town SQLite data. @pomdtr/http_client Attach a postman-like http client to your vals VS Code Extension vt Chrome Extension Tooling Authentication @pomdtr/basicAuth @pomdtr/email_auth @pomdtr/password_auth Sqlite @sqlite/db @pomdtr/sql @pomdtr/kv @postpostscript/sqliteUniverse Blob @stevekrouse/blobAdmin @pomdtr/lowdb Middleware @andreterron/codeOnValTown Testing @pomdtr/test_explorer Api @pomdtr/api @pomdtr/trpc Other @vladimyr/valshot @pomdtr/mdx @pomdtr/serve_readme OpenAI @pomdtr/ask_ai Web Components Val Town Playground CodeMirror

1 3

6

HTTP

- @pomdtr/serve_readme

### OpenAI

- @pomdtr/ask_ai

valwriter_react_clientside

@stevekrouse

[ ] streaming we can't stream into an actual val - we can only write a full piece of text, i guess we can stream back the code so we don't get bored while we wait [ ] send the code of the valwriter back to gpt only if it's related, might need some threads [ ] send errors, logs back to gpt [ ] get screenshots of the output back to gpt [ ] experiment with applying diffs instead of regenerating from scratch every time could also have it as a conversation as the main thing and only the diffs get applied or the whole code gets replaced, maybe tool use it the key here... which does make it seem like a custom gpt may be the better fit...

0

HTTP

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

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

export default basicAuth(async (req) => {

await email({ subject: "Subject line", text: "Body of message" });

// OpenAI

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

const openai = new OpenAI();

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

messages: [

valle_tmp_60836902668989675457109372512279

@janpaul123

@jsxImportSource https://esm.sh/react

0

HTTP

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,

valle_tmp_610457425865436710444833460520275

@janpaul123

@jsxImportSource https://esm.sh/react

0

HTTP

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,

bedtimeStoryMaker

@dthyresson

Bedtime Story Maker Inspired from a RedwoodJS demo I mde last year, this adds generative art powered by Fal to the bedtime story maker. Start writing a story by picking a style (spooky, colofrol, adventurous an animal (penguin, mouse, unicorn, whale ...) a color for the animal 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 summary story 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 geneate a childrens story book image. That's sent to Fal to generate an image. Stories get saved to bedtime_stories in SQLite for viewing, searching and maybe sharing. You then get a bedtime story to enjoy!

3

2

HTTP

* 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 geneate a childrens 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";

VALLErun

@tmcw

The actual code for VALL-E: https://www.val.town/v/janpaul123/VALLE

1

0

HTTP

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.startsWith("gpt")) {

vercelModel = openai(model);

} else {

vercelModel = anthropic(model);

valle_tmp_016298797667905655232930394407136

@janpaul123

@jsxImportSource https://esm.sh/react

0

HTTP

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,

awesome

@stevekrouse

Awesome Val Town An curated list of useful community vals. Feel free to create your own awesome list! Apps @pomdtr/blob_editor @nbbaier/sqliteExplorerApp View and interact with your Val Town SQLite data. @pomdtr/http_client Attach a postman-like http client to your vals VS Code Extension vt Chrome Extension Tooling Authentication @pomdtr/basicAuth @pomdtr/email_auth @pomdtr/password_auth Sqlite @sqlite/db @pomdtr/sql @pomdtr/kv @postpostscript/sqliteUniverse Blob @stevekrouse/blobAdmin @pomdtr/lowdb Middleware @andreterron/codeOnValTown Testing @pomdtr/test_explorer Api @pomdtr/api @pomdtr/trpc Other @vladimyr/valshot @pomdtr/mdx @pomdtr/serve_readme OpenAI @pomdtr/ask_ai Web Components Val Town Playground CodeMirror

1

HTTP

- @pomdtr/serve_readme

### OpenAI

- @pomdtr/ask_ai

inventory

@ejfox

* This val creates an interactive tech stack wizard that generates a video game-style inventory screen. * It uses React for the UI, leverages emoji and Unicode symbols for a visually rich experience, and * incorporates Tailwind CSS for elegant, grayscale styling. * The wizard allows users to select tools, libraries, and APIs, then displays them in a shareable format.

0

HTTP

{ name: "Fly.io", icon: "🪰" },

{ name: "Val.town", icon: "🏘️" },

{ name: "OpenAI", icon: "🧠" },

{ name: "SQLite", icon: "🗃️" },

{ name: "Commander", icon: "🎖️" },

TaylorSwiftMoments

@vawogbemi

@jsxImportSource https://esm.sh/react

2

1

HTTP

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

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

const SCHEMA_VERSION = 2;

const { prompt, era } = await req.json();

const openai = new OpenAI();

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

messages: [

giftSuggestionApp

@trollishka

@jsxImportSource https://esm.sh/react

0

HTTP

const finalBudget = budget.length > 0 ? budget : [budgetOptions[Math.floor(Math.random() * budgetOptions.length)]];

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

const openai = new OpenAI();

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

messages: [{

const content = completion.choices[0].message.content || "{}";

console.log("Raw OpenAI response:", content);

const parsedContent = JSON.parse(content);

} catch (error) {

console.error("Failed to parse OpenAI response:", error);

return new Response(JSON.stringify({ error: "Failed to generate suggestions" }), {

valle_tmp_605448986086057210791953389018616

@janpaul123

@jsxImportSource https://esm.sh/react

0

HTTP

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,