Update src/streamlit_app.py

src/streamlit_app.py

@@ -103,7 +103,7 @@ def get_nutrinutional_info(dish_name, cuisine_type):
             model="gpt-4o-mini",
             messages=[{
                 "role": "user",
-                "content": f"""For the {cuisine_type} dish "{dish_name}", provide estimated nutritional information in JSON format:
+                "content": f"""For the {cuisine_type} dish '{dish_name}', provide estimated nutritional information in JSON format:
                 {{
                     "calories": 350,
                     "protein": 10g,
@@ -125,10 +125,10 @@ def get_nutrinutional_info(dish_name, cuisine_type):
             menu_data = json.loads(menu_text[json_start:json_end])
             return menu_data
         else:
-            return { "calories": "N/A", "protein": "N/A",  "carbs": "N/A", "fat": "N/A", "fiber": "N/A" }
+            return { "calories": 'N/A', "protein": 'N/A',  "carbs": 'N/A', "fat": 'N/A', "fiber": 'N/A' }
 
     except Exception as e:
-        return { "calories": "N/A", "protein": "N/A",  "carbs": "N/A", "fat": "N/A", "fiber": "N/A" }
+        return { "calories": 'N/A', "protein": 'N/A',  "carbs": 'N/A', "fat": 'N/A', "fiber": 'N/A' }
 
 def generate_food_image(dish_name, description, cuisine_type, image_style):
     """Generate food image with enhanced prompting"""
@@ -161,7 +161,7 @@ def generate_food_image(dish_name, description, cuisine_type, image_style):
         }
     }
 
-    selected_style = style_config.get(image_style, style_config["Professional Food Photography"])
+    selected_style = style_config.get(image_style, style_config['Professional Food Photography'])
 
     # Create detailed food photography prompt
     food_prompt = f"""
@@ -170,10 +170,10 @@ Professional food photography of {dish_name} ({cuisine_type} cuisine).
 Dish details: {description}
     
 Photography specifications:
-- {selected_style["lighting"]}
-- {selected_style["background"]}
-- {selected_style["composition"]}
-- {selected_style["quality"]}
+- {selected_style['lighting']}
+- {selected_style['background']}
+- {selected_style['composition']}
+- {selected_style['quality']}
 
 Technical Requirements:
 - High resolution, commercial food photography quality
@@ -227,7 +227,7 @@ if client:
 
     uploaded_file = st.file_uploader(
         "Choose menu image",
-        type=["jpg", "jpeg", "png"],
+        type=['jpg', "jpeg", "png"],
         help="Upload a clear image of your menu with readable text"
     )
 
@@ -241,7 +241,7 @@ if client:
                 if "error" in menu_data:
                     st.error(f"Error extracting menu data: {menu_data['error']}")
                     if "raw_text" in menu_data:
-                        st.text_area("Raw extracted Text", menu_data["raw_text"], height=200)
+                        st.text_area("Raw extracted Text", menu_data['raw_text'], height=200)
 
                 else:
                     st.success("Menu items extracted successfully!")
@@ -253,21 +253,21 @@ if client:
                     col1, col2 = st.columns([2, 1])
 
                     with col1:
-                        st.markdown(f"**Restaurant** {menu_data.get("restaurant_image", "Not detected")}")
-                        st.markdown(f"**Cuisine Type** {menu_data.get("cuisine_type", "Not detected")}")
+                        st.markdown(f"**Restaurant** {menu_data.get('restaurant_image', 'Not detected')}")
+                        st.markdown(f"**Cuisine Type** {menu_data.get('cuisine_type', 'Not detected')}")
 
-                        for category, items in menu_data.get("categories", {}).items():
+                        for category, items in menu_data.get('categories', {}).items():
                             st.markdown(f"**{category}**")
                             for item in items:
                                 st.markdown(f"- {item['name']} - {item.get('price', 'N/A')}")
-                                if item.get("description"):
+                                if item.get('description'):
                                     st.markdown(f"  *{item['description']}*")
 
                     with col2:
                         st.markdown("**Menu Statistics**")
-                        total_items = sum(len(items) for items in menu_data.get("categories", {}).values())
+                        total_items = sum(len(items) for items in menu_data.get('categories', {}).values())
                         st.metric("Total Items", total_items)
-                        st.metric("Categories", len(menu_data.get("categories", {})))
+                        st.metric("Categories", len(menu_data.get('categories', {})))
 
     if "menu_data" in st.session_state:
         st.markdown("---")
@@ -322,7 +322,7 @@ if client:
 
             # get all dishes
             all_dishes = []
-            for category, items in menu_data.get("categories", {}).items():
+            for category, items in menu_data.get('categories', {}).items():
                 for item in items:
                     all_dishes.append((category, item))
 
@@ -330,8 +330,8 @@ if client:
 
             # Generate images and nutrition for each dish
             for i, (category, item) in enumerate(all_dishes):
-                dish_name = item["name"]
-                description = item.get("description", "")
+                dish_name = item['name']
+                description = item.get('description', "")
 
                 status_text.text(f"Generating food photo for {dish_name} ({i+1}/{total_dishes})")
 
@@ -339,13 +339,13 @@ if client:
                 image_bytes, image_url = generate_food_image(
                     dish_name,
                     description,
-                    menu_data.get("cuisine_type", "Fine Dining"),
+                    menu_data.get('cuisine_type', "Fine Dining"),
                     image_style
                 )
 
                 # Get nutritional information
                 if include_nutrition:
-                    nutritional_data[dish_name] = get_nutrinutional_info(dish_name, menu_data.get("cuisine_type", "Fine Dining"))
+                    nutritional_data[dish_name] = get_nutrinutional_info(dish_name, menu_data.get('cuisine_type', "Fine Dining"))
 
                 # update progress
                 progress_bar.progress((i+1)/total_dishes)
@@ -360,12 +360,12 @@ if client:
             # Show individual food photo
             st.markdown("### Generated Food Photos with Nutritional Information")
 
-            for category, items in menu_data.get("categories", {}).items():
+            for category, items in menu_data.get('categories', {}).items():
                 st.markdown(f"**{category}**")
                 cols = st.columns(min(len(items), 3))
 
                 for i, item in enumerate(items):
-                    dish_name = item["name"]
+                    dish_name = item['name']
                     col_index = i % 3
 
                     with cols[col_index]:
@@ -379,10 +379,10 @@ if client:
                         if include_nutrition and dish_name in nutritional_data:
                             nutrition = nutritional_data[dish_name]
                             st.markdown(
-                                f"**Nutrition** {nutrition.get("calories", "N/A")} cal, {nutrition.get("protein", "N/A")} protein"
+                                f"**Nutrition** {nutrition.get('calories', 'N/A')} cal, {nutrition.get('protein', 'N/A')} protein"
                             )
 
-                        if item.get("description"):
+                        if item.get('description'):
                             st.markdown(f"  *{item['description']}*")
 
 
@@ -395,10 +395,10 @@ if client:
 
         timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
 
-        for category, items in menu_data.get("categories", {}).items():
+        for category, items in menu_data.get('categories', {}).items():
             st.markdown(f"**Download {category} Photos:**")
             for item in items:
-                dish_name = item["name"]
+                dish_name = item['name']
                 if dish_name in dish_images:
                     clean_name = re.sub(r'[^a-zA-Z0-9]', '', dish_name)
 
@@ -413,7 +413,7 @@ if client:
                         )
                     col_count += 1
 
-        restaurant_name_clean = re.sub(r'[^a-zA-Z0-9]', '', menu_data.get("restaurant_name", "menu"))
+        restaurant_name_clean = re.sub(r'[^a-zA-Z0-9]', '', menu_data.get('restaurant_name', "menu"))
 
         st.markdown("### Download Menu Report")
 
@@ -427,8 +427,8 @@ if client:
             menu_summary = f"""VISUAL MENU GENERATED REPORT
 Generated: {datetime.now().strftime("%Y-%m-%d %H:%M:%S")}
 
-Restaurant: {menu_data.get("restaurant_name", "N/A")}
-Cuisine Type: {menu_data.get("cuisine_type", "N/A")}
+Restaurant: {menu_data.get('restaurant_name', 'N/A')}
+Cuisine Type: {menu_data.get('cuisine_type', 'N/A')}
 Image Style: {image_style}
 Food Description Display: {layout_style}
 Nutritional Information: {'Included' if include_nutrition else 'Excluded'}
@@ -436,18 +436,18 @@ Nutritional Information: {'Included' if include_nutrition else 'Excluded'}
 Menu Items Generated: {total_dishes}
 """
 
-            for category, items in menu_data.get("categories", {}).items():
+            for category, items in menu_data.get('categories', {}).items():
                 menu_summary += f"\n{category}:\n"
                 for item in items:
-                    menu_summary += f"- {item["name"]} - {item.get('price', 'N/A')}\n"
-                    if include_nutrition and item["name"] in nutritional_data:
-                        nutrition = nutritional_data[item["name"]]
+                    menu_summary += f"- {item['name']} - {item.get('price', 'N/A')}\n"
+                    if include_nutrition and item['name'] in nutritional_data:
+                        nutrition = nutritional_data[item['name']]
                         menu_summary += f"  Nutrition: {nutrition.get('calories', 'N/A')} cal, {nutrition.get('protein', 'N/A')} protein\n"
 
             menu_summary += f"""
 Generation Statistics:
-- Total Items: {sum(len(items) for items in menu_data.get("categories", {}).values())}
-- Categories: {len(menu_data.get("categories", {}))}
+- Total Items: {sum(len(items) for items in menu_data.get('categories', {}).values())}
+- Categories: {len(menu_data.get('categories', {}))}
 - Food Photos Generated: {len(dish_images)}
 - Processing Time: Several minutes