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Integrating OpenAI's DALL-E 3 into Your Bubble App for AI-Generated Images

Author: PlanetNoCodeTime: 2024-01-29 11:00:01

Table of Contents

Introduction to OpenAI's DALL-E 3 for Image Generation

OpenAI have just released DALL-E 3, an AI system that can generate realistic images from text descriptions. In this blog post, we'll show how to connect DALL-E 3 to a Bubble app via the API connector to display AI-generated images.

Before diving into the Bubble integration, let's briefly overview DALL-E 3's capabilities and how to get set up with an API key.

Overview of DALL-E 3 Capabilities

DALL-E 3 stands out for its ability to create coherent, realistic images down to fine details from text prompts. It can generate creative variations on themes while keeping objects recognizable. This makes it useful for tasks like creating avatars, placeholder images, and more. Under the hood, DALL-E 3 was trained on immense datasets pairing images with captions and alt text descriptions. This allows it to learn the relationship between language and visual concepts at scale.

API Key Setup in OpenAI

To call DALL-E 3, you'll need an OpenAI API key. Log into your OpenAI account or create an account if you don't have one. Then go to the API keys page and create a new secret key. Make sure to save this key securely, as it allows access to your OpenAI usage and billing details. With the key handy, we're ready to connect to Bubble.

Connecting DALL-E 3 to Bubble via the API Connector

With the API key set up, let's configure the API connector in our Bubble app to call the DALL-E 3 image generation endpoint.

In the API connector, we'll define the endpoint, headers, and request body following OpenAI's documentation.

Configuring Request Headers

First we need to pass the authorization header with our API key, and specify the content type. Click 'Shared Headers' and add:

Authorization: Bearer {Your API Key}
Content-Type: application/json

Defining the API Request Body

Next we set up the /images/generations endpoint as a POST action. In the request body, we can define a JSON template for the image prompt and parameters. Set num_images to 1 since we only want one image generated per call. Also make the 'prompt' field dynamic via square brackets so we can customize it programmatically later.

Making the Prompt Dynamic

With the basic call defined, let's test it by providing a sample prompt like "a photo of a Cocker Spaniel". We should get back a JSON response with the generated image URL. Now we're ready to connect it to our Bubble frontend and make the prompt customizable!

Displaying AI-Generated Images in the Bubble App

On our Bubble app page, let's add a text input for the prompt, a button to call the API, and a gallery to display results.

We'll store generated images in a repeating group, with fields for the prompt and image binary.

Creating Inputs and Outputs on the Page

Add a multiline text input for the user to provide an image prompt. Next add a button to trigger the API call on click. Below that, create a repeating group bound to a new 'AIImage' database type with 'prompt' and 'image' fields. This will store each generation.

Integrating the API Call into a Workflow

In the button's workflow, call the OpenAI action using the dynamic prompt text. Save the image URL to our storage with a filename matching the prompt. Also save the prompt text itself to the AIImage database record's prompt field before resetting the inputs.

Displaying Results and Resetting

Finally, show a gallery of all previously generated AIImage records so the user can browse the results. When the input is reset, the cycle can begin again to generate another image.

Troubleshooting Common Issues when Connecting OpenAI

With the basics connected, there are some edge cases around handling OpenAI API responses and managing storage that are good to understand before productionizing this in an app.

Handling API Response Data

Since we request one image but OpenAI returns a list, we have to handle extracting just the first result's URL to save the image binary. Always examine the full API response structure so you can properly parse the desired fields.

Storing Images Locally

While OpenAI hosts generated images temporarily, it's insecure to rely on their URLs indefinitely. Instead we save each image to the Bubble database under our control. This avoids losing images if they get cleaned up from OpenAI's servers after an unknown TTL.

Conclusion and Next Steps for Implementation

That wraps up a basic example of leveraging OpenAI's DALL-E 3 AI image generator within a Bubble application!

Some next steps would be allowing users more control over image styles and parameters before calling the API. The prompts could also integrate dynamic content from elsewhere in the app.


Q: How do I get an API key for OpenAI?
A: You can generate a new API key by signing up at openai.com and accessing your account settings. Be sure to keep this key private.

Q: What is the benefit of saving images locally in Bubble?
A: Saving OpenAI images locally through Bubble ensures you maintain access to them independently of OpenAI's own storage limits.

Q: How can I customize the image generation further?
A: You can fine tune the prompts provided to DALL-E 3 for more specific outputs. Additionally, multiple images can be requested in a single call.