📚 Documentação inicial do ALETHEIA

- MANUAL-PRODUTO.md: Manual do usuário final
- MANUAL-VENDAS.md: Estratégia comercial e vendas
- MANUAL-TECNICO.md: Infraestrutura e deploy
- README.md: Visão geral do projeto

backend/app/routers/scan.py

@@ -0,0 +1,106 @@
+import json
+from datetime import datetime, timezone, date
+from fastapi import APIRouter, Depends, HTTPException
+from sqlalchemy.ext.asyncio import AsyncSession
+from sqlalchemy import select, func
+from app.database import get_db
+from app.models.user import User
+from app.models.product import Product
+from app.models.scan import Scan
+from app.schemas.scan import ScanRequest, ScanResult, ScanHistoryItem
+from app.utils.security import get_current_user
+from app.integrations.open_food_facts import fetch_product
+from app.integrations.openai_client import analyze_product
+from app.config import settings
+from app.services.seed import SEED_PRODUCTS
+
+router = APIRouter(prefix="/api", tags=["scan"])
+
+@router.post("/scan", response_model=ScanResult)
+async def scan_product(req: ScanRequest, user: User = Depends(get_current_user), db: AsyncSession = Depends(get_db)):
+    # Rate limit check
+    if not user.is_premium:
+        today_start = datetime.now(timezone.utc).replace(hour=0, minute=0, second=0, microsecond=0)
+        result = await db.execute(
+            select(func.count(Scan.id)).where(Scan.user_id == user.id, Scan.scanned_at >= today_start)
+        )
+        count = result.scalar()
+        if count >= settings.FREE_SCAN_LIMIT:
+            raise HTTPException(status_code=429, detail=f"Limite de {settings.FREE_SCAN_LIMIT} scans/dia atingido. Faça upgrade para Premium!")
+
+    # Check local cache
+    result = await db.execute(select(Product).where(Product.barcode == req.barcode))
+    product = result.scalar_one_or_none()
+    
+    product_data = None
+    source = "cache"
+    
+    if product:
+        product_data = {
+            "name": product.name, "brand": product.brand, "category": product.category,
+            "ingredients_text": product.ingredients_text, "nutri_score": product.nutri_score,
+            "nova_group": product.nova_group, "nutrition": json.loads(product.nutrition_json or "{}"),
+            "image_url": product.image_url,
+        }
+    else:
+        # Check seed data
+        if req.barcode in SEED_PRODUCTS:
+            product_data = SEED_PRODUCTS[req.barcode].copy()
+            source = "seed"
+        else:
+            # Fetch from Open Food Facts
+            product_data = await fetch_product(req.barcode)
+            source = "open_food_facts"
+        
+        if product_data:
+            new_product = Product(
+                barcode=req.barcode, name=product_data.get("name"), brand=product_data.get("brand"),
+                category=product_data.get("category"), ingredients_text=product_data.get("ingredients_text"),
+                nutri_score=product_data.get("nutri_score"), nova_group=product_data.get("nova_group"),
+                nutrition_json=json.dumps(product_data.get("nutrition", {})),
+                image_url=product_data.get("image_url", ""),
+            )
+            db.add(new_product)
+            await db.commit()
+    
+    if not product_data:
+        raise HTTPException(status_code=404, detail="Produto não encontrado. Tente inserir manualmente.")
+
+    # AI Analysis
+    analysis = await analyze_product(product_data)
+    
+    # Save scan
+    scan = Scan(
+        user_id=user.id, barcode=req.barcode, product_name=product_data.get("name"),
+        brand=product_data.get("brand"), score=analysis.get("score", 50),
+        summary=analysis.get("summary", ""), analysis_json=json.dumps(analysis),
+    )
+    db.add(scan)
+    await db.commit()
+
+    return ScanResult(
+        barcode=req.barcode,
+        product_name=product_data.get("name"),
+        brand=product_data.get("brand"),
+        category=product_data.get("category"),
+        image_url=product_data.get("image_url"),
+        score=analysis.get("score", 50),
+        summary=analysis.get("summary", ""),
+        positives=analysis.get("positives", []),
+        negatives=analysis.get("negatives", []),
+        ingredients=analysis.get("ingredients", []),
+        nutri_score=product_data.get("nutri_score"),
+        nova_group=product_data.get("nova_group"),
+        source=source,
+    )
+
+@router.get("/history", response_model=list[ScanHistoryItem])
+async def get_history(user: User = Depends(get_current_user), db: AsyncSession = Depends(get_db)):
+    result = await db.execute(
+        select(Scan).where(Scan.user_id == user.id).order_by(Scan.scanned_at.desc()).limit(50)
+    )
+    scans = result.scalars().all()
+    return [ScanHistoryItem(
+        id=s.id, barcode=s.barcode, product_name=s.product_name,
+        brand=s.brand, score=s.score, scanned_at=s.scanned_at
+    ) for s in scans]