According to studies by the NRDC and Harvard Law, approximately 91% of individuals discard perfectly good food due to confusing labels like “sell by” and “best by.” This contributes significantly to food waste, which eventually rots in landfills and emits potent greenhouse gases. Eatelligent is an online platform designed to combat the climate crisis by helping users manage food waste. Users can track their groceries and generates custom recipes that specifically prioritize those soon-to-expire ingredients.
- Sustainability
- Best SlugHacks
- Use of GenAI
- Most Start-up Potential
- Best Use of MongoDB
Frontend: TypeScript, JavaScript, CSS (React/Vite)
Database: MongoDB Atlas to store user preferences, ingredients, and recipe data.
Authentication: Firebase Authentication for secure sign-up, login, and session management.
LLM: Python, HuggingFace (Llama-3.1-8B-Instruct) to generate dynamic, user-specific recipes based on inventory.
We originally envisioned Eatelligent as a mobile application. However, due to the complexities of converting a MERN stack web app into a mobile environment within the hackathon time constraints, we pivoted to a high-quality web application.
As first-time users of the MERN stack, we gained deep experience in connecting a full-stack architecture with external services. We successfully integrated Firebase for security and LLMs for intelligent response generation, learning how to manage data flow between the database and the AI.
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Mobile Conversion: Porting the web experience to a native mobile app.
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Computer Vision: Implementing an image-recognition system so users can photograph groceries to auto-extract data instead of manual entry.
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Deployment: Launching a live version via Vercel.
- Start the Server Navigate to the server directory in your terminal: python recipe_generation.py
- Run these two commands: cd server npm install node --env-file=.env server
- Start the Client Open a new terminal window and navigate to the client directory: cd client npm run dev
- Access the App Click the local link provided in your terminal (e.g., http://localhost:5173) to view the live project.