AI Boyfriend

CalHacks 10.0 submission.

Setup

# Instructions for starting the server locally

# Install
npm install && npm run build

# Start server
npm run dev

# Start server and watch for changes
npm run dev:watch

Environment File

YELP_API_KEY="..."
OPENAI_API_KEY="..."
GOOGLE_MAPS_API_KEY="..."

Devpost

https://devpost.com/software/ai-boyfriend

Inspiration

The inspiration for AI Boyfriend came from the common dilemma of not knowing what to eat. We wanted to create a tool that not only suggests meals but also understands and adapts to individual preferences, dietary needs, and moods, making meal selection a stress-free experience.

What it does

AI Boyfriend is an app that serves as a digital culinary guide. It uses smart algorithms and a series of intuitive questions generated by LLMs to understand a user's preferences, then curates personalized meal suggestions. It simplifies the decision-making process for meals by providing targeted, tailored recommendations.

How we built it

We developed AI Boyfriend by using Large Language Models (LLMs) to generate interactive, conversational questionnaires. The app integrates with Yelp's API to offer a wide range of meal suggestions. The user-friendly interface was designed with a focus on simplicity and ease of use.

Challenges we ran into

One of the biggest challenges was refining the AI to accurately interpret and respond to a diverse set of dietary preferences and restrictions. Ensuring the app consistently provided relevant and varied suggestions without overwhelming the user was also a significant hurdle.

Accomplishments that we're proud of

As newcomers to hacking, we're proud of successfully developing an app that integrates LLMs for meal decision-making. Despite our limited experience, we overcame technical challenges, learning and applying different APIs rapidly.

Our teamwork stands out – different skills and backgrounds merged effectively, crucial for the app’s success and positive user feedback, especially on its intuitive interface. This achievement in a high-pressure, hackathon environment not only demonstrates our technical growth but also our strong collaborative dynamic.

What we learned

Through this project, we learned a great deal about user experience design, advanced machine learning techniques, and the intricacies of dietary preferences. We also gained insights into managing and analyzing large data sets to provide meaningful recommendations.

What's next for AI Boyfriend

AI Boyfriend is set to become a full-fledged lifestyle assistant, expanding its scope to include event and activity recommendations:

• Event Integration: It will suggest personalized events like concerts and exhibitions, based on user interests.
• Activity Suggestions: The app will recommend activities tailored to users’ preferences and current conditions like weather.
• Social Planning: Users can plan and coordinate group events, considering everyone's preferences and schedules.
• Customized Itineraries: AI Boyfriend will create tailored itineraries combining dining and activities for full-day experiences.
• Feedback-Driven Learning: User reviews will refine the AI’s suggestions, ensuring relevancy and satisfaction.
• Local Partnerships: Collaborating with businesses for exclusive deals and experiences, enhancing the entertainment options.
• Adaptive Recommendations: The app will evolve with users, providing ideas for family, romantic, or solo adventures based on life stages.

This upgrade will transform AI Boyfriend into a comprehensive guide for dining, events, and activities, adapting to the dynamic needs of modern lifestyles.