🧠 Intelligent Nutri – AI-Powered Recipe & Nutrition Assistant

Eat smarter. Cook faster. Live healthier.

Intelligent Nutri is a personalized AI-driven platform that helps users find recipes, analyze nutrition, generate shopping lists, and chat with a virtual food assistant — all based on their dietary needs and preferences.

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📦 Project Structure

intelligent-nutri/
│
├── frontend/               # All UI code here
│   ├── index.html
│   ├── preferences.html
│   ├── chatbot.html
│   └── js/
│       ├── app.js          # JS for preferences form & search
│       └── chatbot.js      # JS for AI chat interface
│   └── css/
│       └── style.css      
│
├── backend/                # All Flask-related backend code
│   ├── main.py             # Entry point — define routes here
│   ├── llm_utils.py        # Functions to generate prompts & call Gemini/OpenAI
│   ├── db_utils.py         # Functions to interact with SQLite (CRUD)
│   └── vector_utils.py     # Handle FAISS search & embeddings
│
├── database/
│   ├── schema.sql          # Create tables
│   ├── init_db.py          # Script to create and initialize database
│   └── seed_data.py        # Preload recipes from dataset (Kaggle, etc.)
│
└── requirements.txt

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⚙️ Tech Stack

Layer	Tech Used
Frontend	HTML, CSS, JS, Bootstrap
Backend	Python Flask, REST APIs
Database	SQLite3, FAISS (Vector DB)
AI/NLP	OpenAI / Gemini via API, Sentence Transformers

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🚀 Quick Start

1. Clone the Repo

git clone https://github.com/your-username/intelligent-nutri.git
cd intelligent-nutri

2. Backend Setup (Flask)

cd backend
python3 -m venv venv
source venv/bin/activate
pip install -r ../requirements.txt

# Start the server
python run.py

3. Frontend Access

Open any of the following in your browser:

• frontend/index.html → Main dashboard
• frontend/preferences.html → User preferences form
• frontend/chatbot.html → Chat with the AI chef

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🧠 Core Features

• 🧾 Preferences-Based Personalization: Tailored recipes based on user's dietary needs and health goals.
• 🔍 Recipe Search: Search by ingredients or dishes, powered by vector similarity search.
• 🧑‍🍳 AI Chatbot: Talk to a virtual chef using LLM-based prompts.
• 🛒 Shopping List Generator: (Optional) Exportable ingredient lists for selected recipes.
• 🧠 Agentic AI Flow (Optional): Voice control & web search coming soon.

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👥 Team & Collaboration Guidelines

Branch Naming

• main: Production-ready
• dev: Ongoing development
• feature/<feature-name>: Individual tasks

Suggested Roles

• Frontend UI
• Form & preference logic
• Chatbot & prompt design
• Recipe search integration
• Vector DB & embeddings
• Integration & DevOps

Git Workflow

# Create a new branch
git checkout -b feature/<your-feature>

# Make changes and commit
git add .
git commit -m "Add: <describe your feature>"

# Push and create PR
git push origin feature/<your-feature>

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📌 To-Do / Milestones

• User Authentication
• Preferences Form & Storage
• Recipe Search via API & Dataset
• Chatbot Integration with LLM
• Vector DB Setup
• Dashboard UI
• Deployment (Optional: Vercel + Render)

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📄 License

MIT License

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🧠 Inspired by

Foodie brains, AI chefs, and real-world meal struggles.

“Good food is the foundation of genuine happiness.” – Auguste Escoffier