Padho Label 🥗

Scan any packaged product — know instantly whether it's good for your body, and why.

Padho Label ("padho" = read in Hindi) is an offline-first React Native (Expo) app for the Indian market. Point it at a barcode and it looks the product up on Open Food Facts / Open Beauty Facts, then computes a health score personalised to your profile — diet, goals, and conditions like diabetes, hypertension, or PCOS — and explains the verdict in plain language.

No account. No tracking. All your data lives on your device.

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What it does

• Barcode scan → instant verdict. A grade (A–E) and a 0–100 Padho Score, personalised to your health profile when one is set up — with a "why this grade" breakdown.
• Allergen & diet enforcement (v5). Your declared allergies (gluten, dairy, nuts, soy, egg) and diet (veg / vegan / Jain / satvik / eggitarian) are checked against every ingredient list — conflicts surface as unmissable alert banners.
• Sugar in teaspoons (v5). 56g/100g means nothing; "14 teaspoons" lands. Per serving when the pack declares one.
• Smarter added-sugar analysis (v5). Intrinsic lactose/fructose (plain milk, dahi, 100% juice) is no longer punished like added sugar — the engine reads the ingredient list to tell the difference.
• Nutrition breakdown. Per-100g values with bars against your personal daily limits.
• Ingredient & additive analysis. Flags 80+ FSSAI-notified additives (E/INS numbers) by concern level, with notes; a separate database for cosmetics.
• "For You" insights. Plain-language, rule-based bullets (no LLM, no hallucination) tailored to your goals and conditions.
• Label OCR fallback. Product not in the database? Snap the label — v5 extracts the ingredients list as well as the nutrition numbers (via the free OCR.space API), and lets you name unknown products so they're remembered properly.
• ~100-product Indian seed catalog (v5). Big-brand biscuits, namkeen, noodles, chocolates, drinks, dairy, spreads and more ship in the bundle — so Compare, Healthier Swaps and search work offline from the first launch, and every scan you make grows the on-device catalog further.
• Healthier swaps. Every result shows better-scored alternatives from the same category, with a Swiggy Instamart hand-off to buy them.
• Pantry & history. Track what you keep at home and review past scans. Everything is stored locally.

Architecture

• Offline-first, no backend. All user state (profile, history, pantry, favourites) is in device AsyncStorage. There is no login and nothing is synced to a server.

• Three-tier product lookup (getProductByBarcode), each tier optional/graceful:

  scan → curated catalog (Airtable)  →  Open Food Facts  →  OCR the label
         your D2C / new-edition SKUs     world+India+beauty   any product, editable
  

  The curated catalog is read-only and opt-in (see env below); with no token set the app is a plain OFF + OCR scanner. The analysis engine is identical regardless of source.

• Self-healing intelligence (src/services/intelligence/): a local-first resolution waterfall (barcode → brand+name+qty → same-product line → fuzzy) over a bundled seed catalog plus a learned cache. Any product resolved via Open Food Facts or OCR is written back, so the slow path never runs twice on a device, and queued to grow the shared catalog. It powers the Compare screen — ranks options for your profile, leading with the axis that matters (sugar for diabetes, sodium for hypertension…). See docs/INTELLIGENCE.md and USER_GUIDE.md.

• Scoring engine (src/services/ratingEngine.ts): a transparent Nutri-Score base plus a personalised 0–100 score derived from HealthConstraints computed from the user profile.

• OCR (src/services/ocrNutrition.ts): image → text via OCR.space, then a regex parser. The recognition step is isolated so an on-device engine (e.g. Google ML Kit) can drop in later without touching the parser.

src/
  screens/      Home · Scan · Pantry · Profile · History · Result · IngredientsSnap · Settings · Onboarding
  services/     api · ratingEngine · ocrNutrition · additivesService · beautyService
                history · favorites · pantryService · userProfileService · flagDerivation
  types/        shared TypeScript types
  theme.ts      colours, typography, spacing

Getting started

npm install
cp .env.example .env      # optional — only needed for label OCR
npm run android           # or: npm run ios / npm start

Environment

All variables are optional — with none set, the app is a fully working OFF + OCR scanner.

Variable	Purpose
EXPO_PUBLIC_AIRTABLE_BASE_ID	Curated catalog base (appdFbiM5AogN1muz = the "Padho Label" base).
EXPO_PUBLIC_AIRTABLE_TOKEN	Read-only, base-scoped Airtable PAT (data.records:read). Bundled into the client — never use a broad token.
EXPO_PUBLIC_AIRTABLE_TABLE	Catalog table name (default Products).
EXPO_PUBLIC_OCRSPACE_API_KEY	Free OCR.space key (25k req/month) for the label-scan fallback. Falls back to the rate-limited helloworld demo key if unset.

Scripts

• npm start — Expo dev server
• npm run android / npm run ios
• npm test — Jest unit tests (scoring, OCR parsing, additive detection, intelligence)
• npm run build:catalog — regenerate the bundled catalog from scripts/sources/*.json
• npm run promote <file> — fold an exported contribution queue into the catalog source
• npm run android build pipeline & Play Store submission: see SETUP.md

Quality

npx tsc --noEmit   # type-check (clean)
npm test           # 18 tests, all green

Disclaimer

Padho Label is an informational tool, not medical advice. Always consult a qualified professional for dietary decisions. Nutrition data is community-sourced from Open Food Facts and may be incomplete or out of date.

Contains information from Open Food Facts, made available under the Open Database License (ODbL).