Search

export let npmExample = (async () => {

const { HUMAN_PROMPT, AI_PROMPT, Client } = await import(

"npm:@anthropic-ai/sdk"

); // The Lodash library exported as ES modules.

const client = new Client(

"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"

const prompt = `${HUMAN_PROMPT}

当你的女朋友说“滚, 不要拿AI跟我对话.”。你应该如何安慰她？

${AI_PROMPT}`;

console.log("size of prompt", prompt.length);

import { askAI } from "https://esm.town/v/pomdtr/ask_ai";

await askAI("Send me an email with a random joke");

const exa = new Exa(Deno.env.get("EXA_API_KEY"));

export const exaSearch = async ({ query, type, useAutoprompt, numResults, text, summary=true, highlights }) => {

const result = await exa.searchAndContents(

query,

type: type || "auto" || "neural",

useAutoprompt: useAutoprompt || true,

numResults: 10,

highlights: highlights || {

numSentences: 3,

highlightsPerUrl: 1,

Using Vercel AI SDK

import { ModelProvider, modelProvider } from "https://esm.town/v/yawnxyz/ai";

let response = await modelProvider.gen({

prompt: "hello, who am I speaking to?",

provider: "google",

} as any);

console.log("res:", response);

import * as util from "https://code.agentscript.org/src/utils.js";

const model = new Model();

await model.startup();

model.setup();

console.log("Running for 500 steps.");

util.repeat(500, model.step);

const sample = util.sampleModel(model);

console.log(sample);

This val demonstrates the [creation of an API](https://www.val.town/v/nbbaier/dbToAPI) with a programmatically generated set of data instead of an existing Val Town [lowdb](https://www.val.town/v/pomdtr/lowdb) instance.

const mock = () => {

const data = { users: [], posts: [], random: {} };

for (let i = 0; i < 25; i++) {

const user: string = faker.person.fullName(); // Rowan Nikolaus

const userSplit: string[] = user.split(" ");

const email: string = userSplit[0].endsWith(".")

? userSplit[1].toLowerCase() + "." + userSplit[2].toLowerCase() + "@"

+ faker.internet.domainName()

: userSplit[0].toLowerCase() + "." + user.split(" ")[1].toLowerCase() + "@"

const replicate = new Replicate({

auth: Deno.env.get("REPLICATE_API_KEY"),

export default serve({

async *handleMessage(req) {

const lastMsg = req.query.at(-1);

if (lastMsg && lastMsg.attachments.length !== 2) {

yield events.replace("No image recieved");

yield html;

yield events.done();

return;

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

fal.config({

// Can also be auto-configured using environment variables:

credentials: Deno.env.get("FAL_KEY"),

const prompt = "a cute and happy dog";

const result: any = await fal.run("fal-ai/fast-lightning-sdxl", { input: { prompt } });

console.log(result.images[0].url);

export default serve({

async *handleMessage(req) {

yield "hello";

await sleep(1000);

yield events.replace("goodbye");

await sleep(1000);

yield events.error({

allow_retry: true,

text: "ooops!",

yield events.done();

console.info("Launching browser...");

const apiKey = Deno.env.get("BROWSERBASE_API_KEY");

if (!apiKey) {

console.error("BROWSERBASE_API_KEY environment variable is not set");

Deno.exit(1);

try {

const browser = await chromium.connectOverCDP(

Example of using the [are.na](https://dev.are.na/documentation/channels#Block43472) API to get the contents of an Are.na board - specifically my fun board that showcases websites with that "glossy black style."

All you need is [fetch](https://developer.mozilla.org/en-US/docs/Web/API/Fetch_API) to make this happen!

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

export let arenaApiExample = (async () => {

const resp = await fetch(

"http://api.are.na/v2/channels/project-logs",

const json = await resp.json();

console.log(json);

return json;

* INITIALIZE API

const api = new GptApi({

url: "https://vlad-tempsimplegptexample.web.val.run",

title: "Some API",

description: "API for something",

version: "1.0.0",

const ResponseCommandSchema = z.object({

feedback: z.string().describe("Feedback regarding submitted action"),

data: z.string().optional().describe("Additional data related to the given command"),

import { Application } from "https://deno.land/x/oak/mod.ts";

const app = new Application();

app.use((ctx) => {

ctx.response.body = "Hello Val Town!";

export default app.fetch;

Example of using the [are.na](https://dev.are.na/documentation/channels#Block43472) API to get the contents of an Are.na board - specifically my fun board that showcases websites with that "glossy black style."

All you need is [fetch](https://developer.mozilla.org/en-US/docs/Web/API/Fetch_API) to make this happen!

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

export let arenaApiExample = (async () => {

const resp = await fetch(

"http://api.are.na/v2/channels/that-glassy-dark-design-style",

const json = await resp.json();

return json;

const token = Deno.env.get("tanaInputAPI");

export const tanaSave = async (req: Request) => {

const app = new Hono();

app.get("/save", async c => {

let { text, url } = c.req.query();

const payload: APIPlainNode = {

name: text,

children: [

{ name: "child 1" },

{ type: "field", attributeId: "cwi23sOzRSh8" },