Embeddings Demo

Understand how data is converted to embeddings

Built With

• Next.js + tailwind
• OpenAI's text-embedding-3-small model
• Node version 20 or higher

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Start the project

Requires Node version 20+

From the project root directory, run the following command.

npm install

Set environment variables

Make sure you have populated a .env.local file with your OpenAI API key:

OPENAI_API_KEY="your_openai_api_key_here"

Start the app.

npm run dev

Project structure

In this example we opted to use Next.js and the app router, which colocates the frontend and backend code in a single repository.

Frontend Client

The frontend uses Next.js and tailwind to allow users to enter free form text. This text is split by word on the client-side and then converted to tokens by the tiktoken library when the user clicks the Convert text to embeddings button.

OpenAI's text-embedding-3-small model extracts the features of the text you provide it and returns vectors representing these features.

Backend API route

This project exposes an API route: /api/embeddings:

import { NextRequest, NextResponse } from 'next/server';
import OpenAI from 'openai';

const openai = new OpenAI({
  apiKey: process.env.OPENAI_API_KEY,
});

export async function POST(req: NextRequest) {
  const { inputText } = await req.json();

  try {
    const response = await openai.embeddings.create({
      model: 'text-embedding-3-small',
      input: inputText,
    });

    const generatedEmbeddings = response.data[0].embedding;
    console.log(`Generated embeddings: %o`, generatedEmbeddings);

    return NextResponse.json({ embeddings: generatedEmbeddings }, { status: 200 });
  } catch (error) {
    console.error('Error generating embeddings:', error);
    return NextResponse.json({ error }, { status: 500 });
  }
}