# Using Bun 1.0 for Serving APIs with Vercel AI SDK and OpenAI

Just a few days ago, the much-anticipated [**Bun 1.0**](https://bun.sh/blog/bun-v1.0) 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.

![](https://cdn.hashnode.com/res/hashnode/image/upload/v1717164811979/6f11ce6e-e76c-43e3-980d-68edd5e778e0.png)

[Bun 1.0](https://bun.sh/blog/bun-v1.0)

Here are the features of **Bun 1.0** in case you missed it!

<iframe src="https://www.youtube.com/embed/BsnCpESUEqM?feature=oembed" width="700" height="393" frameborder="0" scrolling="no"></iframe>

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**](https://bun.sh/) and the [**Vercel AI SDK**](https://vercel.com/blog/introducing-the-vercel-ai-sdk). The API serves chat completion requests from the chat web application I built using [**NextJS 13**](https://nextjs.org/blog/next-13) and [**shadcn/ui**](https://ui.shadcn.com/).

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  
const stream = OpenAIStream(response);  
  
// Return the streaming response  
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.

<iframe src="https://www.youtube.com/embed/ASDJ0V9r4OM?feature=oembed" width="1192" height="894" frameborder="0" scrolling="no"></iframe>

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  
                const stream = OpenAIStream(response);  
  
                // Return the streaming response  
                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}\`);

If you like my article, you can follow me and subscribe here in Medium for more. You can also support me by [buying me a coffee!](https://www.buymeacoffee.com/melvindave)

[![](https://cdn.hashnode.com/res/hashnode/image/upload/v1717164813352/ac99a8f4-ffed-4fc4-b791-a9bf5ede8e4a.png)](https://www.buymeacoffee.com/melvindave)

You can also follow me in my social media. Cheers!

[🐦 twitter.com/donvito](http://twitter.com/donvito)  
[🔗 linkedin.com/in/melvinvivas](https://www.linkedin.com/in/melvinvivas)  
[👾 github.com/donvito](https://github.com/donvito)  
[🔗 donvitocodes.com](https://www.donvitocodes.com/)