---
id: 'examples-openai'
title: 'Generating OpenAI GPT3 completions'
description: 'Generate GPT text completions using OpenAI and Supabase Edge Functions.'
subtitle: 'Generate GPT text completions using OpenAI and Supabase Edge Functions.'
video: 'https://www.youtube-nocookie.com/v/29p8kIqyU_Y'
tocVideo: '29p8kIqyU_Y'
---

OpenAI provides a [completions API](https://platform.openai.com/docs/api-reference/completions) that allows you to use their generative GPT models in your own applications.

OpenAI's API is intended to be used from the server-side. Supabase offers Edge Functions to make it easy to interact with third party APIs like OpenAI.

## Setup Supabase project

If you haven't already, [install the Supabase CLI](/docs/guides/cli) and initialize your project:

```shell
supabase init
```

## Create edge function

Scaffold a new edge function called `openai` by running:

```shell
supabase functions new openai
```

A new edge function will now exist under `./supabase/functions/openai/index.ts`.

We'll design the function to take your user's query (via POST request) and forward it to OpenAI's API.

```ts index.ts
import OpenAI from 'https://deno.land/x/openai@v4.24.0/mod.ts'

Deno.serve(async (req) => {
  const { query } = await req.json()
  const apiKey = Deno.env.get('OPENAI_API_KEY')
  const openai = new OpenAI({
    apiKey: apiKey,
  })

  // Documentation here: https://github.com/openai/openai-node
  const chatCompletion = await openai.chat.completions.create({
    messages: [{ role: 'user', content: query }],
    // Choose model from here: https://platform.openai.com/docs/models
    model: 'gpt-3.5-turbo',
    stream: false,
  })

  const reply = chatCompletion.choices[0].message.content

  return new Response(reply, {
    headers: { 'Content-Type': 'text/plain' },
  })
})
```

Note that we are setting `stream` to `false` which will wait until the entire response is complete before returning. If you wish to stream GPT's response word-by-word back to your client, set `stream` to `true`.

## Create OpenAI key

You may have noticed we were passing `OPENAI_API_KEY` in the Authorization header to OpenAI. To generate this key, go to https://platform.openai.com/account/api-keys and create a new secret key.

After getting the key, copy it into a new file called `.env.local` in your `./supabase` folder:

```
OPENAI_API_KEY=your-key-here
```

## Run locally

Serve the edge function locally by running:

```bash
supabase functions serve --env-file ./supabase/.env.local --no-verify-jwt
```

Notice how we are passing in the `.env.local` file.

Use cURL or Postman to make a POST request to http://localhost:54321/functions/v1/openai.

```bash
curl -i --location --request POST http://localhost:54321/functions/v1/openai \
  --header 'Content-Type: application/json' \
  --data '{"query":"What is Supabase?"}'
```

You should see a GPT response come back from OpenAI!

## Deploy

Deploy your function to the cloud by runnning:

```bash
supabase functions deploy --no-verify-jwt openai
supabase secrets set --env-file ./supabase/.env.local
```

## Go deeper

If you're interesting in learning how to use this to build your own ChatGPT, read [the blog post](/blog/chatgpt-supabase-docs) and check out the video:

<div class="video-container">
  <iframe
    src="https://www.youtube-nocookie.com/embed/Yhtjd7yGGGA"
    frameBorder="1"
    allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture"
    allowFullScreen
  ></iframe>
</div>