LookBook

Lookbook: Your ultimate makeup + skincare AI. We instantly create your perfect routine based on your skin, preferences, and daily needs. Get ready for truly personalized beauty.

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Inspiration

As women from all walks of life, we understand the joy and sometimes the frustration of expressing ourselves through makeup. We've all faced that moment of confusion, wondering which products are truly right for us. That's why we created LookBook: to empower every woman to confidently craft their ideal makeup and skincare routine. LookBook eliminates the guesswork. Our platform generates a customized routine that’s unique to you, taking into account your skin condition, allergies, preferred brands, the location, the date, and the occasion. It's about celebrating your individual beauty and giving you the tools to feel confident and authentically you, every single day.

What it does

LookBook simplifies and perfects your makeup and skincare routine. Users begin by creating a detailed personal profile, including their skin conditions, allergies, existing product inventory, and preferred brands. To create a custom look, users simply input the location, date, and type of occasion. LookBook then leverages this information – analyzing the weather conditions for the specified location and time, the nature of the occasion, and the user's unique skin profile – to generate a customized 8-step makeup and skincare routine. Users have full control: if a recommended product isn't quite right, they can easily click to regenerate replacements until they're completely satisfied. Finally, once the perfect routine is formulated, users can save their custom look, along with all its recommended products, to their personal dashboard for future reference.

How we built it

We developed Lookbook collaboratively using VSCode Live Share, beginning with a clear outline for an intuitive user experience. Our frontend was created with React, leveraging JavaScript and CSS to achieve a clean, minimalistic, and visually appealing aesthetic. To bridge the frontend with our backend, we utilized Flask. The core intelligence of Lookbook is driven by Mistral AI. The flow: User Input & Weather Data: After gathering the user's location and date for an occasion, we integrated a weather API to retrieve real-time data on temperature, humidity, wind, and precipitation. AI Prompt Generation: Combining the user's detailed profile (skin conditions, allergies, owned products, preferred brands) with the occasion specifics and real-time weather data, we formulated a precise AI prompt for Mistral AI. Routine Generation & Refinement: Mistral AI then generated an initial makeup and skincare routine with product recommendations. We displayed this to the user, allowing them to easily regenerate replacements for any disliked products by sending new prompts to Mistral AI. Saving Routines: Once the user was fully satisfied with their personalized routine, all selected products were transferred and saved to their personal dashboard on the backend for convenient future access.

Challenges we ran into

We encountered some challenges in seamlessly connecting our frontend and backend due to the combination of different languages and tools. Initially, getting user input to save correctly and displaying the generated routines on the frontend proved difficult. Properly getting our output displayed on the frontend was also hard for us. However, through experimentation with JavaScript, CSS, and Flask, we successfully overcame these hurdles. Another specific challenge was refining the regeneration process to accurately replace disliked products with options that truly aligned with the user's preferences. We also struggled with integrating APIs and using AI to generate proper routines that fit what we wanted to show on the frontend.

Accomplishments that we're proud of

We’re proud to have created a frontend that is perfectly compatible with the backend, creating a seamless user experience. As beginner hackers, we are pleased to have brought our vision to life using our previous Python skills and newly gained React skills.

What we learned

Through building Lookbook, we gained valuable experience in integrating React with Python, and effectively separating our frontend and backend codebases. We also mastered the art of efficiently dividing work using VS Code LiveShare and pushing/pulling work to and from Github. Beyond the significant coding experience gained during VenusHacks, this project taught us crucial skills in collaboration, communicating innovative ideas, and the importance of compromise within a team.

What's next for LookBook

In the future, we hope that users can sign in and out of their accounts to save and relook at their looks. We also plan to include images of the actual products and links to purchase the products in the routine once the user finalizes a routine.

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