Inspiration
Our inspiration for this project stemmed from the challenges of cooking meals in college. Most online recipes require specific ingredients, while our software suggests meals based on the main ingredients you already have.
What it does
Our project utilizes Gemini machine learning to process user-input ingredients and generate a personalized recipe. It also securely stores the user's login details.
How we built it
We developed it using Python, Django, CSS, and HTML. We used Git for version control and collaboration and CodePen for front-end testing. Additionally, we employed Gemini's text generation feature to produce specific recipes for the user.
Challenges we ran into
Some of the challenges we encountered included merging the front end and back end, using the Gemini API for the first time, and learning how to use Django.
Accomplishments that we're proud of
We are proud of our accomplishments, such as successfully developing a final product using new concepts like AI. Additionally, we are pleased to have completed HowdyHack with only two group members.
What we learned
We learned that sometimes it's best to start with a simple working model and then expand it by adding more functionality.
What's Next for Reveille's Recipes
Next time we revise Reveille's Recipes, we would like to add more cooking options for each recipe (e.g., checklist, timer, etc.) and variations of ingredients to make them more GMO, Vegan, and Vegetarian friendly. We would like to output multiple recipes so the user has a wider selection. With each of these recipes the user will also be able to see an image of an example of how the recipe would look after completion. The user would also be able to access past generated recipes.
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