Update app.py

app.py

@@ -4,25 +4,33 @@ import pandas as pd
 # Load menu data from Excel file
 def load_menu(file_path="menu.xlsx"):
     """
-    Load menu data from an Excel file dynamically based on column headers.
+    Load menu data from an Excel file and dynamically map its columns to required fields.
     """
     menu_df = pd.read_excel(file_path)
     # Normalize column names (strip spaces and make lowercase)
     menu_df.columns = menu_df.columns.str.strip().str.lower()
     
-    # Check for required columns
-    required_columns = {"name", "price", "description", "image"}
-    if not required_columns.issubset(set(menu_df.columns)):
-        raise ValueError(f"Excel file is missing one or more required columns: {required_columns}")
+    # Map dynamic column names to required fields
+    column_mapping = {
+        "name": next((col for col in menu_df.columns if "name" in col), None),
+        "price": next((col for col in menu_df.columns if "price" in col), None),
+        "description": next((col for col in menu_df.columns if "description" in col), None),
+        "image": next((col for col in menu_df.columns if "image" in col), None),
+    }
+
+    # Ensure all required columns are present
+    missing_columns = [key for key, col in column_mapping.items() if col is None]
+    if missing_columns:
+        raise ValueError(f"Excel file is missing one or more required columns: {missing_columns}")
     
     # Map data to required structure
     menu = []
     for _, row in menu_df.iterrows():
         menu.append({
-            "name": row["name"],
-            "price": row["price"],
-            "description": row["description"],
-            "image": row["image"]
+            "name": row[column_mapping["name"]],
+            "price": row[column_mapping["price"]],
+            "description": row[column_mapping["description"]],
+            "image": row[column_mapping["image"]],
         })
     return menu