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🍽️ FridgeFusion – AI Recipe Generation & Nutrition Assistant

FridgeFusion is a full-stack AI-powered cooking and meal planning assistant that transforms food images into complete recipes with nutrition insights.

Using Gemini Vision, the system identifies ingredients directly from images, then generates personalized recipes through a FastAPI + Groq-hosted LLaMA pipeline, supporting dietary preferences, cuisine styles, and multiple recipe outputs.

It also provides goal-based meal recommendations (weight loss, high-protein, diabetic-friendly) and exports recipes into beautifully formatted PDFs.

🚀 Key Highlights

  • 📸 Ingredient detection from food images using Gemini Vision
  • 🤖 AI-powered recipe generation with LLaMA (Groq)
  • 🥗 Diet & preference-driven cooking suggestions
  • 🧪 Nutrition breakdown per serving
  • 🧾 Automated PDF export of recipes + instructions
  • 🔥 Fusion Recipe Lab for creative multi-style outputs
  • 🎯 Goal-based meal planning engine (fitness + health focused)

✨ Core Features

✅ Ingredient Recognition (Gemini Vision)

Upload a food image and Pic2Plate instantly detects:

  • Ingredients present in the dish
  • Food components for recipe building
  • Vision-based understanding for better accuracy

🍳 AI Recipe Generation Pipeline

Pic2Plate generates complete recipes with:

  • Step-by-step cooking instructions
  • Multiple recipe variations
  • Cuisine selection (Indian, Italian, etc.)
  • Diet control (Veg, Keto, High-protein, etc.)

Powered by:

  • FastAPI backend
  • Groq-hosted LLaMA model

🧪 Nutrition Assistant

Every recipe includes:

  • Calories per serving
  • Protein / Carbs / Fats breakdown
  • Health-focused meal insights

🎯 Goal-Based Recommendation Engine

Smart meal suggestions for:

  • Weight-loss plans
  • High-protein muscle diets
  • Diabetic-friendly recipes
  • Balanced nutrition goals

🧾 PDF Export (Recipe Report)

Users can export recipes as formatted PDFs including:

  • Ingredients list
  • Cooking steps
  • Nutrition facts
  • Personalized notes

Perfect for saving or sharing meal plans.

🛠️ Tech Stack

Layer Technology
Frontend Next.js
Backend FastAPI (Python)
Vision AI Gemini Vision API
LLM Engine LLaMA via Groq
Nutrition Automated per-serving analysis
Output PDF Export + Recipe Formatting

⚙️ Installation & Setup

Follow these steps to run Pic2Plate locally:

1️⃣ Clone the Repository

git clone https://github.com/Jayesh251203/Pic2Plate.git
cd Pic2Plate

🖥️ Frontend Setup (Next.js)

cd frontend
npm install
npm run dev

Frontend will run at:

http://localhost:3000

⚡ Backend Setup (FastAPI) Create Virtual Environment

cd backend
python -m venv venv

Activate it:

Windows

venv\Scripts\activate

Linux/Mac

source venv/bin/activate

Install Dependencies

pip install -r requirements.txt

Run FastAPI Server

uvicorn main:app --reload

Backend will run at:

http://localhost:8000

🔑 Environment Variables

Create a .env file inside the backend folder: Add Your API key's there to use.

⭐ Support

If you like this project, consider giving it a ⭐ on GitHub — it really helps!

THANKYOU !