Val Town Code SearchReturn to Val Town

2Use the Vercel AI SDK in your Vals.
3
4**Note**: you must add your OpenAI key to your Val Town [Env variables](https://www.val.town/settings/environment-variables) under `OPENAI_API_KEY`. If you would like to specify a different name for your API Key, you can [create a custom OpenAI provider](https://sdk.vercel.ai/providers/ai-sdk-providers/openai#provider-instance) with the `createOpenAI` function.
5
6Prefer another AI provider? Use [any supported provider](https://sdk.vercel.ai/providers/ai-sdk-providers) by changing just two lines of code!

1import { OpenAI } from "https://esm.town/v/std/openai";
2export default async function(req: Request): Promise<Response> {
3  const openai = new OpenAI();
4  const stream = await openai.chat.completions.create({
5    stream: true,
6    messages: [{ role: "user", content: "Write a poem in the style of beowulf about the DMV" }],

1import { OpenAI } from "https://esm.town/v/std/openai";
2
3export default async function(req: Request): Promise<Response> {
4  const openai = new OpenAI();
5  const stream = await openai.chat.completions.create({
6    stream: true,
7    messages: [{

1Migrated from folder: Archive/openAIStreamingExample

1import { blob } from "https://esm.town/v/std/blob?v=12";
2import OpenAI from "npm:openai";
3
4const openai = new OpenAI();
5
6const getCacheKey = (url: string): string => {
90  let pageResult = "";
91
92  // // 2. Do one OpenAI inference to expand that URL to a longer page description
93  const pageDescriptionStream = await openai.chat.completions.create({
94    model: "gpt-4o",
95    messages: [{
127
128    // 3. Generate the page
129    const stream = await openai.chat.completions.create({
130      model: "gpt-4o",
131      messages: [{

8    }
9
10    const endpoint = 'https://api.openai.com/v1/chat/completions';
11    const model = 'gpt-4';
12

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.

1# OpenAI Streaming - Assistant and Threads
2
3An example of using OpenAI to stream back a chat with an assistant. This example sends two messages to the assistant and streams back the responses when they come in.
4
5Example response:

1import OpenAI from "npm:openai";
2const openai = new OpenAI();
3import process from "node:process";
4
5// Define our assistant.
6const assistant = await openai.beta.assistants.create({
7  name: "Val Tutor",
8  instructions: `You are a personal Val tutor. 
14
15// Create a thread to chat in.
16const thread = await openai.beta.threads.create();
17
18// These are the messages we'll send to the assistant.
44          }, 100);
45
46          const message = await openai.beta.threads.messages.create(
47            thread.id,
48            { role: "user", content: messages[i] },
49          );
50
51          const run = openai.beta.threads.runs.stream(thread.id, {
52            assistant_id: assistant.id,
53            // Make sure we only display messages we haven't seen yet.