3import { basicAuth } from "https://esm.town/v/pomdtr/basicAuth?v=62";
4import { fetchText } from "https://esm.town/v/stevekrouse/fetchText";
5import { chat } from "https://esm.town/v/stevekrouse/openai";
6import cronstrue from "npm:cronstrue";
7import { Hono } from "npm:hono@3";
117 await email({ subject: "Subject line", text: "Body of message" });
118
119 // OpenAI
120 import { OpenAI } from "https://esm.town/v/std/openai";
121 const openai = new OpenAI();
122 const completion = await openai.chat.completions.create({
123 messages: [
124 { role: "user", content: "Say hello in a creative way" },
126. Uses EPA's ranking to classify the severity of the score (ie "Unhealthy for Sensitive Groups")
13
14It uses blob storage to cache the openai location id for your location string to skip a couple steps for the next time.
15
16## Example usage
1import { OpenAI } from "https://esm.town/v/std/openai";
2
3const openai = new OpenAI();
4
5/**
58
59/**
60 * Gets the response from the OpenAI language model.
61 * @param {string} prompt - The prompt for the language model.
62 * @returns {Promise<string>} - The response from the language model.
63 */
64async function getLlmResponse(prompt: string) {
65 const completion = await openai.chat.completions.create({
66 "messages": [
67 { "role": "user", "content": prompt },
1# openAiProxy
2
3## Overview
4
5This val is a proxy server that interacts with the OpenAI API to generate responses based on prompts in the request body. The function handles incoming HTTP POST requests, processes the prompt, and returns a response generated by the LLM.
6
7## Prerequisites
8
9- Server-side: (Optional) An active OpenAI API key
10- Client-side: Something that can make POST requests (browser code, Postman, cURL, another Val, etc)
11
25
26```sh
27curl -X POST https://ashryanio-openaiproxy.web.val.run -H "Content-Type: application/json" -d '{"prompt": "Hello, OpenAI!"}'
28```
29
31
32- **Content-Type**: application/json
33- **Body**: JSON object containing the response from the OpenAI language model.
34
35#### Example Response
1# ChatGPT Implemented in Val Town
2
3Demonstrated how to use assistants and threads with the OpenAI SDK and how to stream the response with Server-Sent Events.
4
5<p align=center>
1/** @jsxImportSource https://esm.sh/react */
2import OpenAI from "npm:openai";
3import { renderToString } from "npm:react-dom/server";
4
5// This uses by personal API key, you'll need to provide your own if
6// you fork this. We'll be adding support to the std/openai lib soon!
7const openai = new OpenAI();
8import { Hono } from "npm:hono@3";
9
38 });
39
40 // Setup the SSE connection and stream back the response. OpenAI handles determining
41 // which message is the correct response based on what was last read from the
42 // thread. This is likely vulnerable to race conditions.
58const app = new Hono();
59app.get("/", async (c) => {
60 const thread = await openai.beta.threads.create();
61 const assistant = await openai.beta.assistants.create({
62 name: "",
63 instructions:
114app.post("/post-message", async (c) => {
115 let message = await c.req.text();
116 await openai.beta.threads.messages.create(
117 c.req.query("threadId"),
118 { role: "user", content: message },
132 ));
133 };
134 const run = openai.beta.threads.runs.stream(threadId, {
135 assistant_id: assistantId,
136 // Make sure we only display messages we haven't seen yet.
1import puppeteer from "https://deno.land/x/puppeteer@16.2.0/mod.ts";
2import { OpenAI } from "https://esm.town/v/std/openai?v=4";
3import { Browserbase } from "npm:@browserbasehq/sdk";
4
31
32// ask chat gpt for list of concert dates
33const openai = new OpenAI();
34
35const completion = await openai.chat.completions.create({
36 messages: [
37 { role: "system", content: "Return concert dates as JSON array. No code fences." },
89 console.log(`Created ${fileResponses.length} ${gzip ? "gzip" : ""} files`);
90
91 return new Response(JSON.stringify({ openaiFileResponse: fileResponses }), {
92 status: 200,
93 headers: { "Content-Type": "application/json" },
1# OpenAI - [Docs ↗](https://docs.val.town/std/openai)
2
3Use OpenAI's chat completion API with [`std/openai`](https://www.val.town/v/std/openai). This integration enables access to OpenAI's language models without needing to acquire API keys.
4
5For free Val Town users, [all calls are sent to `gpt-3.5-turbo`](https://www.val.town/v/std/openaiproxy?v=5#L69).
6
7Streaming is not yet supported. Upvote the [HTTP response streaming feature request](https://github.com/val-town/val-town-product/discussions/14) if you need it!
10
11```ts title="Example" val
12import { OpenAI } from "https://esm.town/v/std/openai";
13
14const openai = new OpenAI();
15
16const completion = await openai.chat.completions.create({
17 messages: [
18 { role: "user", content: "Say hello in a creative way" },
27## Limits
28
29While our wrapper simplifies the integration of OpenAI, there are a few limitations to keep in mind:
30
31* **Usage Quota**: We limit each user to 10 requests per minute.
34If these limits are too low, let us know! You can also get around the limitation by using your own keys:
35
361. Create your own API key on [OpenAI's website](https://platform.openai.com/api-keys)
372. Create an [environment variable](https://www.val.town/settings/environment-variables?adding=true) named `OPENAI_API_KEY`
383. Use the `OpenAI` client from `npm:openai`:
39
40```ts title="Example" val
41import { OpenAI } from "npm:openai";
42
43const openai = new OpenAI();
44```
45
46
47[📝 Edit docs](https://github.com/val-town/val-town-docs/edit/main/src/content/docs/std/openai.mdx)
1# ChatGPT Implemented in Val Town
2
3Demonstrated how to use assistants and threads with the OpenAI SDK and how to stream the response with Server-Sent Events.
4
5<p align=center>
