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Use Case

AI-generated art and digital content

Generative AI models like Language Model (LLM) and image generators offer tremendous potential in creating AI-generated art and digital content.

For instance, ChatGPT, a variant of LLM, can create original textual content such as poetry, stories or digital ad copies. It learns patterns from human-written texts and generates similar sentences, allowing for a considerable level of creativity.

Image generators utilize models like GANs (Generative Adversarial Networks) to produce visual art. OpenAI's DALL-E, for instance, synthesizes images from textual descriptions, even those that have no clear real-world analogs. This makes it possible to create concept art or unique designs based on abstract or surreal prompts.

Similarly, models like MuseNet use Transformer-based architectures to generate novel music compositions stemming from a variety of styles and epochs, further extending the artistic reach of AI models.

How to build with Clevis

Text Input

Prompt the user to enter a topic or keyword

Prompt ChatGPT

ChatGPT will generate a list of relevant AI-generated art and digital content based on the user's input

HTTP Request

Fetch additional information about the selected art pieces from external APIs

Generate Image (DALL-E)

Generate a unique AI-generated image based on the selected art piece

Display Output

Display the retrieved information and generated image in a user-friendly format

This is an explanation of an exemplary application that you can build using Clevis, designed to produce and showcase AI-generated art and digital content. The application works in a series of clearly defined steps.

First, the app initiates with a Text Input step that prompts the user to enter a topic or a keyword. The app then utilizes OpenAI's ChatGPT in the ChatGPT step to generate a range of AI-created art and digital content relevant to the user's input. This helps provide users with a personalized experience tailored to their interests.

Following this, our example app performs an Http Request to fetch supplementary information about the chosen artworks from external APIs. This ensures a richer, more detailed output for every selected item.

Next, during the DALL·E step, the application uses the DALL-E model to generate a unique AI-created image based on the selected art piece, further enhancing the user interactivity with the app.

Finally, in the Display Output stage, the retrieved information and the AI-generated image are presented to the user in an intuitive and user-friendly format.

You can design similar applications within the same domain using the Clevis platform.

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