Cómo Usar el SDK de Vercel para Aplicaciones Web con Inteligencia Artificial

Do you want to learn how to implement artificial intelligence in your web applications easily? With Vercel's SDK, it is now easier to create applications integrating artificial intelligence models such as OpenAI. This resource offers you a set of practical tools in JavaScript and TypeScript to connect to various models, from GPT to options like Azure or AWS, in a simple and efficient way.

What does the Vercel SDK for Artificial Intelligence offer?

The SDK created by Vercel allows developers to work with artificial intelligence through a package that makes it easy to connect to multiple models from a single interface. Its advantages include:

• Compatibility with different artificial intelligence providers.
• A simple API for sending requests and receiving responses.
• Practical examples and clear documentation for quick implementations.

What applications can you build using this technology?

Using this SDK, you can develop innovative projects such as:

• Interactive chats powered by artificial intelligence.
• Applications that analyze and interpret PDF documents.
• Useful tools such as automatic color palette generators based on text and ideas.

Why choose Next.js and when to use Astro?

Next.js has become widely popular for its ease and efficiency in building robust and dynamic React-based applications. Opt for Next.js especially when:

• You need to build complex administrative interfaces.
• You require connections to multiple APIs.
• You will be developing applications that go beyond simple static content.

However, for websites more focused on static content, simple informational pages or small landing pages, Astro may be a better choice for its optimized performance and easy configuration.

How to configure the Vercel SDK in your app with Next.js?

Setting up the Vercel SDK in your Next.js app is quite simple:

1. Install the necessary package:

npm install ai

1. Create an API path with a simple function to run your custom prompt.

import  { OpenAI  } from 'openai';import  { OpenAIStream, StreamingTextResponse  } from 'ai';const openai  = new OpenAI({ apiKey: process.env.OPENAI_API_KEY  });export async function  POST(req: Request)  {  const  { prompt  }  = await req.json();  const response  = await openai.chat.completions.create({    model: 'gpt-4-turbo',    messages: [{ role: 'user', content: prompt  }],  });  return new StreamingTextResponse(OpenAIStream(response));} }

With this API route, you will send requests to your preferred artificial intelligence model from Next.js.

How to easily integrate artificial intelligence into your frontend?

For quick and easy integration into React, use native SDK functions like useCompletion:

import  { useCompletion  } from 'ai/react';export default function MyComponent()  {  const  { completion, handleSubmit, input, setInput  }  = useCompletion({    api: '/api/get-palette',   });  return  (    <form  onSubmit={handleSubmit}>      <input         value={input}         onChange={(e)  => setInput(e.target.value)}      />      <button  type="submit">Generate Palette</button>      {completion  && <div>{completion}</div>}    </form>   );}

This allows you to handle interactions easily on the client side, substantially reducing the code needed to integrate artificial intelligence models thanks to automatic and optimized productions.

Do you want to try these tools?

Remember that to use specific models you need an API key that you can get from OpenAI Platform or your preferred provider. Carefully configure your environment variables and enjoy experimenting with the latest in artificial intelligence applied to web development.

If you have created similar projects or have questions about this process, let us know in the comments!