• 

  User Interface

EZ-Outfit: A Location Based Outfit Suggestion App

Inspiration

I wanted to create an app that can makes the process of choosing the right outfit for different occasions and weather conditions easier and more fun, by using the power of generative widgets in the PartyRock playground.

What it does

EZ-Outfit is an app that suggests outfits based on the user’s location, preferences, and occasion. The user can input their gender, style, and event type, and the app will generate a suitable outfit for the weather conditions. The app takes into account the current weather and temperature at the user’s location, and adjusts the outfit accordingly.

How we built it

EZ-Outfit was created using the PartyRock AWS platform, which provides us with a variety of generative LLM widgets. We used the following widgets:

• Location Widget: uses the user’s provided location to fetch the weather and temperature information.

• Activity Widget: uses an input to collect the user’s occasion preferences to improve the outfit suggestion.

• Outfit Suggestion Widget: uses the inputs from the Activity and Location Widgets, including weather and temperature data to generate an outfit. The widget also uses natural language generation to provide a description for each outfit.

Challenges we ran into

• Ensuring that the outfits generated by the Outfit Widget are coherent, diverse, and appropriate for the user’s preferences and weather conditions.

Accomplishments that we're proud of

• Creating an app that can generate personalized and location-based outfit suggestions using generative LLM widgets.

• Completing the project within the time limit of the hackathon.

What we learned

• How to use the PartyRock AWS hackathon platform and the generative LLM widgets to create dynamic and realistic content.

• Using prompts as instructions to tune the outputs of generative widgets to meet desired outputs.

Built With

• amazon-web-services
• partyrockaws