Backend scores updates on products

app/api/routers/brands.py

@@ -86,6 +86,18 @@ def _row_to_product_out(row: dict, fallback_brand: str) -> ProductOut:
     if fssai is not None:
         fssai = str(fssai).strip() or None
 
+    # NUMERIC arrives as decimal.Decimal, which Pydantic would coerce but JSON
+    # would not. Converted here so 0.0 survives - `or None` would turn a real
+    # score of zero into "not scored", and zero is a valid health score.
+    def _score(key: str) -> Optional[float]:
+        raw = row.get(key)
+        if raw is None:
+            return None
+        try:
+            return float(raw)
+        except (TypeError, ValueError):
+            return None
+
     return ProductOut(
         image_id=image_id,
         image_url=primary_url,
@@ -108,6 +120,8 @@ def _row_to_product_out(row: dict, fallback_brand: str) -> ProductOut:
         selling_price=sp,
         barcode=bcd,
         barcode_type=bcd_type,
+        nutrition_score=_score("nutrition_score"),
+        health_score=_score("health_score"),
     )
 
 

app/api/routers/upload.py

@@ -569,6 +569,8 @@ async def upload_nutrition_file(file: UploadFile = File(...)) -> Dict[str, Any]:
     skipped = 0
     skipped_non_consumable = 0
     status_counts = {"verified": 0, "partial": 0, "unavailable": 0}
+    # Which brands to mirror onto the brand tables once the import commits.
+    touched_brands: set = set()
 
     try:
         with conn, conn.cursor() as cur:
@@ -752,6 +754,7 @@ async def upload_nutrition_file(file: UploadFile = File(...)) -> Dict[str, Any]:
                     )
 
                 imported_count += 1
+                touched_brands.add(brand)
 
     except HTTPException:
         raise
@@ -761,6 +764,14 @@ async def upload_nutrition_file(file: UploadFile = File(...)) -> Dict[str, Any]:
     finally:
         conn.close()
 
+    # Mirror onto the brand tables, so a consumer reading product rows directly
+    # sees an uploaded score too. After the commit and outside the try, because
+    # this must never turn a successful import into a 500 - sync_after_write
+    # swallows its own failures for the same reason.
+    if touched_brands:
+        from app.services.nutrition_score_sync import sync_after_write
+        sync_after_write(sorted(touched_brands))
+
     return _finish(
         file.filename, len(df), imported_count, errors, skipped,
         "nutritional intelligence items",