Just a few days ago, the much-anticipated Bun 1.0 was launched, bringing a fresh perspective to the world of JavaScript. This new Javascript runtime and toolkit, etc. promises the fastest execution times and better developer experience.
Although I come from a backend development background and wouldn’t consider myself a seasoned JavaScript expert, I’ve always had an interest in exploring the various tools and frameworks. So, when Bun 1.0 made its debut a few days ago, I felt compelled to dive in and see what it had to offer, especially given that this realm is somewhat new to me.
Since I am playing around with OpenAI, I created a simple API using Bun and the Vercel AI SDK. The API serves chat completion requests from the chat web application I built using NextJS 13 and shadcn/ui.
It was really nice since it supports streaming out of the box! Since I already implemented the API in Next13, it was pretty straightforward to port the code to Bun.
const response = await openai.chat.completions.create({
model: 'gpt-3.5-turbo',
messages,
stream: true,
});
// Assuming OpenAIStream is a function that processes the response for streaming - not working yet
const stream = OpenAIStream(response);
// Return the streaming response - not working yet
return new StreamingTextResponse(stream,
{ headers: corsResponseHeaders });
Here’s a demo of the Chat application I built. The API being consumed by the web application in the left is the one created using Bun.
Here's the full source code of the API I built using Bun and Vercel AI SDK.
import OpenAI from 'openai';
import { OpenAIStream, StreamingTextResponse } from 'ai';
const openai = new OpenAI({ apiKey: Bun.env.OPENAI_API_KEY });
const corsResponseHeaders = {
"Access-Control-Allow-Origin": "*",
"Access-Control-Allow-Methods": "POST, GET, OPTIONS",
"Access-Control-Allow-Headers": "X-PINGOTHER, Content-Type",
"Access-Control-Max-Age": "86400"
}
const server = Bun.serve({
port: 3001,
async fetch(req) {
if (req.method === 'POST') {
try {
const { messages } = await req.json();
const response = await openai.chat.completions.create({
model: 'gpt-3.5-turbo',
messages,
stream: true,
});
// Assuming OpenAIStream is a function that processes the response for streaming - not working yet
const stream = OpenAIStream(response);
// Return the streaming response - not working yet
return new StreamingTextResponse(stream,
{ headers: corsResponseHeaders });
} catch (error) {
console.log("Error: ", error);
// Return an error response
return new Response("Internal Server Error",
{
status: 500,
headers: corsResponseHeaders
},
);
}
} else {
// Handle other request methods or return a default response
return new Response("Not Found", { status: 404,
headers: corsResponseHeaders });
}
},
});
console.log(`Listening on localhost: ${server.port}`);
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[reposted from] https://techblogs.donvitocodes.com/using-bun-1-0-for-serving-apis-with-vercel-ai-sdk-and-openai-e6d01fedd2ca
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