NutraSpec

AI-powered ingredient risk scoring. Snap a photo of any food label, get a personalized safety analysis based on your allergies, dietary preferences, and health goals.

Built at PatriotHacks 2026.

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What It Does

1. Scan — Point your camera at any ingredient label. Google Gemini extracts every ingredient from the image.
2. Analyze — Gemini grades ingredients against your allergy profile, dietary restrictions, and health goals.
3. Score — Get a 0–100 risk score with clear conflict breakdowns (Low / Medium / High Risk) and a human-readable summary.
4. Listen — Hear a spoken summary of the results via ElevenLabs text-to-speech.
5. Cache — Analysis results are cached by (ingredients + profile) hash for consistency and speed.
6. Allergen check — Deterministic backup flags allergen derivatives (e.g. peanut butter when you have peanut allergy).

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Tech Stack

Layer	Technology
Frontend	React 19, TypeScript, Vite, Tailwind CSS v4, Lucide Icons, React Router
Backend	Python 3.11+, FastAPI, Pydantic, Uvicorn
AI / Vision	Google Gemini API (vision extraction + risk analysis — no separate scoring engine)
Voice	ElevenLabs API (text-to-speech for result explanations)
Database	Supabase (PostgreSQL — user profiles, analysis cache)

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Project Structure

FoodFinder.AI/
├── .env.example              ← copy to .env and fill in keys
├── .gitignore
├── README.md                 ← you are here
├── SETUP.md                  ← detailed setup & troubleshooting guide
│
├── backend/
│   ├── requirements.txt
│   ├── migrations/
│   │   ├── 001_user_profiles.sql   ← user_profiles table
│   │   └── 002_analysis_cache.sql  ← analysis_cache table
│   └── app/
│       ├── main.py           ← FastAPI entrypoint, CORS, route registration, dotenv
│       ├── config.py         ← env vars (GEMINI, SUPABASE, etc.)
│       ├── database.py       ← Supabase client (service role)
│       ├── dependencies.py   ← auth: Supabase API + optional JWT verification
│       ├── models.py         ← Pydantic: AnalyzeResult, FlaggedIngredient, ProfileUpdatePayload
│       ├── routes/
│       │   ├── __init__.py
│       │   ├── analyze.py    ← POST /analyze (image, include_audio, profile_json)
│       │   ├── user.py       ← GET/PUT /user/profile (auth required)
│       │   └── health.py     ← GET /health
│       ├── services/
│       │   ├── __init__.py
│       │   ├── gemini_service.py      ← vision + analysis (retry on 429)
│       │   ├── elevenlabs_service.py  ← text → speech (MP3 bytes)
│       │   ├── supabase_service.py    ← user profiles + analysis cache
│       │   └── allergen_check.py     ← deterministic allergen keyword check
│       └── core/
│           ├── __init__.py
│           ├── exceptions.py  ← custom error classes
│           ├── logger.py     ← logging helper
│           └── utils.py      ← to_title_case, etc.
│
└── frontend/
    ├── package.json
    ├── vite.config.ts
    ├── postcss.config.js
    ├── index.html
    └── src/
        ├── main.tsx
        ├── App.tsx
        ├── lib/
        │   ├── supabase.ts   ← Supabase client
        │   └── utils.ts      ← cn() utility (clsx + tailwind-merge)
        ├── components/
        │   ├── landing/
        │   │   ├── Navbar.tsx
        │   │   ├── Hero.tsx
        │   │   ├── About.tsx
        │   │   ├── Features.tsx
        │   │   ├── HowItWorks.tsx
        │   │   ├── TechStack.tsx
        │   │   ├── BentoShowcase.tsx
        │   │   ├── CTA.tsx
        │   │   └── Footer.tsx
        │   ├── ui/
        │   │   └── button.tsx
        │   ├── CameraView.tsx
        │   ├── ScoreCircle.tsx
        │   ├── RiskBadge.tsx
        │   ├── ConflictList.tsx
        │   ├── AudioPlayer.tsx
        │   ├── ARResultOverlay.tsx
        │   └── LoadingOverlay.tsx
        ├── screens/
        │   ├── LandingScreen.tsx
        │   ├── ScanScreen.tsx
        │   ├── ResultScreen.tsx
        │   ├── ProfileScreen.tsx
        │   ├── SettingsScreen.tsx
        │   └── AuthScreen.tsx
        ├── navigation/
        │   └── RootNavigator.tsx
        ├── context/
        │   └── UserContext.tsx
        ├── hooks/
        │   ├── useAnalyze.ts
        │   ├── useCameraPermission.ts
        │   └── useUserProfile.ts
        ├── services/
        │   ├── api.ts
        │   ├── analyzeService.ts
        │   └── userService.ts
        ├── types/
        │   ├── apiTypes.ts
        │   ├── scanTypes.ts
        │   └── userTypes.ts
        ├── utils/
        │   ├── constants.ts
        │   ├── errorHandler.ts
        │   └── formatters.ts
        └── styles/
            ├── globalStyles.css   ← Tailwind v4 theme (white & orange)
            └── theme.ts

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## Quick Start

### Prerequisites

- Python 3.11+
- Node.js 20+
- [Gemini API key](https://aistudio.google.com/apikey)
- [ElevenLabs API key](https://elevenlabs.io/)
- [Supabase project](https://supabase.com/) (URL, service role key, anon key)

### 1. Clone and configure

```bash
git clone <your-repo-url>
cd FoodFinder.AI
cp .env.example .env
# Edit .env with your real API keys

2. Backend

cd backend
python -m venv venv
source venv/bin/activate        # Windows: venv\Scripts\activate
pip install -r requirements.txt

Run the migrations in Supabase SQL Editor (in order):

• migrations/001_user_profiles.sql
• migrations/002_analysis_cache.sql

uvicorn app.main:app --reload --host 0.0.0.0 --port 8000

3. Frontend

cd frontend
npm install
npm run dev

Open http://localhost:5173 in your browser.

See SETUP.md for detailed instructions, mobile testing over LAN, and troubleshooting.

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Environment Variables

Variable	Purpose
GEMINI_API_KEY	Google Gemini API (vision + analysis)
ELEVENLABS_API_KEY	ElevenLabs API for text-to-speech
SUPABASE_URL	Supabase project URL
SUPABASE_SERVICE_ROLE_KEY	Supabase service role key (backend operations)
SUPABASE_JWT_SECRET	Optional. Local JWT verification (faster). Omit to use Supabase API.
VITE_SUPABASE_ANON_KEY	Supabase anon key (frontend auth + backend token verification)
BACKEND_HOST	Uvicorn bind host (default: 0.0.0.0)
BACKEND_PORT	Uvicorn bind port (default: 8000)
VITE_API_URL	Frontend → backend URL (production)
VITE_SUPABASE_URL	Supabase URL (frontend)

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License

This project was built for PatriotHacks 2026. No license specified.