FitLook is a full-stack AI-powered fashion assistant platform that helps users discover personalized outfit suggestions, analyze their fashion style, try on clothes virtually, and track style trends using cutting-edge technologies.
FitLook is designed for fashion lovers and shoppers who want to simplify the process of choosing the right outfit for the right occasion. With integrated AI capabilities such as outfit analysis, image generation, and virtual try-on, FitLook delivers a highly personalized and immersive fashion experience.
It consists of three major modules:
- Backend API – Built with Java Spring Boot for managing user data, outfit suggestions, and storing images.
- AI Module – Built with Python and LangChain using Gemini Pro Vision for deep outfit analysis and image-based recommendations.
- Frontend App – Built with React Native for a smooth mobile experience.
- Java 17
- Spring Boot
- REST APIs
- Python 3.11+
- LangChain
- Gemini 2.5 Pro
- Kling AI Image API
- Kling AI Try-On API
- React Native
- Expo
- Firebase Authentication (optional)
- Axios
[Frontend (React Native)]
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[Backend (Spring Boot REST API)]
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[AI Module (LangChain + Gemini)]
git clone https://github.com/edameral/FitLook.git
cd FitLookcd backend
./mvnw spring-boot:runcd ai_modul
pip install -r requirements.txt
python main.pycd fitlook-app
npm install
npx expo startCreate the following environment files before running:
GOOGLE_API_KEY=your_google_gemini_api_key
GEMINI_MODEL=models/
- User uploads an outfit photo in the mobile app
- Frontend sends the image to the Python AI module
- LangChain+Gemini analyzes the outfit and generates suggestions
- Backend stores and serves suggestion data
- Frontend shows the results and allows further actions (shopping links, virtual try-on, etc.)
This project is licensed under the MIT License. See the LICENSE file for details.
Made with by @edameral & @aligöktuğkaplan