GPT4All and Stable Diffusion: Build Your Product Idea Maker

Build with Stable Diffusion and GPT-4-All: A Step-by-Step Guide

Are you seeking inspiration for new product ideas? Do you want to create an AI application but find yourself struggling to identify a problem to solve? This tutorial will guide you through creating a Stable Diffusion application integrated with GPT-4-All, enabling you to generate innovative product ideas for free. In this tutorial, we’ll build a Flask app that utilizes GPT-4-All locally to generate a name and description for your product, while also employing the Stable Diffusion API to create a compelling featured image. Furthermore, we will design a simple user interface (UI) that allows access to the app through your web browser.

What is GPT-4-All?

GPT-4-All is an open-source chatbot developed by Nomic AI, trained on a vast corpus of assistant interactions. This includes various formats, such as word problems, multi-turn dialogues, code samples, poems, songs, and stories. Its versatility makes it a powerful tool for generating creative content.

Setting Up Your Project

To get started, first create a directory for your project. You will also need an API Key from Stable Diffusion — which you can obtain for free after registering at DreamStudio.

Once you have your API Key, create a .env file and paste it there along with your environment variables.

Install Required Libraries

Before coding, make sure to install the necessary libraries. Once that’s done, create a file named app.py and let’s start coding!

Building the Application

First, we need to import all the necessary libraries and load the environment variables. Next, we can initialize a Flask app with CORS enabled for cross-origin requests.

Defining the API Endpoint

Let’s define an endpoint that listens for a product idea and transforms it into a tangible product concept. We will utilize GPT-4-All to generate the product name and description. When you run the app for the first time, you will likely need to download a model; this can take some time depending on your internet connection. We will utilize the gpt4all-j-v1.3-groovy model for this tutorial.

Next, we will use the product name generated by GPT-4-All to call the Stable Diffusion API and generate an image for our new product. The /generate endpoint will accept a query string in the URL and respond with a JSON containing the name, description, and image path. For example, accessing http://localhost:8000/generate?prompt=Cooking%20app will provide ideas for a "Cooking app".

Generating the Image

We will define a generate_image function to format the prompt for Stable Diffusion and save the generated image in the project’s root directory. This function will return the image path, enabling its inclusion in the final JSON response.

We’ll also define a utility function, check_and_create_filename(filename), to create a new filename for the image file if one already exists. This prevents overwriting existing images with the same name.

Finally, we will start an HTTP server to expose our API endpoint.

Running the Application

Now, we can run our app! Test it by sending a request to your endpoint. Open your browser and modify the text as desired, ensuring to use %20 instead of spaces in your prompt. For example:

Congratulations!

You’ve just built your API! You can now run it locally or deploy it to receive JSON responses with product ideas applicable to your favorite frontend framework.

Bonus: Creating a Frontend for the API

As a small bonus, let’s create an index.html file utilizing jQuery and AJAX to enhance the user experience. This HTML file will feature a text input and loading button that calls our API. To access your page, navigate to /path_to_project_directory/index.html in your browser.

Final Thoughts on Building with Stable Diffusion and GPT-4-All

Our app serves as a fantastic starting point for generating creative ideas for new products. It has the potential for improvement, such as adding more styles and refining prompts. You could also explore different models like Mosaic’s MPT and determine which one suits your needs best. I hope this tutorial helps ignite your creativity and inspire great ideas! You can find the final code repository here.