🚀 Major Update: 89.82% Accuracy Model + Professional UI

allergen_info.json

@@ -0,0 +1,118 @@
+{
+  "grilled_salmon": {
+    "common_allergens": ["Fish"],
+    "may_contain": []
+  },
+  "pizza": {
+    "common_allergens": ["Gluten", "Dairy", "Wheat"],
+    "may_contain": ["Egg", "Soy"]
+  },
+  "chicken_curry": {
+    "common_allergens": [],
+    "may_contain": ["Dairy", "Nuts"]
+  },
+  "caesar_salad": {
+    "common_allergens": ["Dairy", "Egg"],
+    "may_contain": ["Gluten", "Wheat"]
+  },
+  "hamburger": {
+    "common_allergens": ["Gluten", "Dairy", "Wheat"],
+    "may_contain": ["Egg", "Soy", "Sesame"]
+  },
+  "sushi": {
+    "common_allergens": ["Fish"],
+    "may_contain": ["Shellfish", "Soy", "Sesame"]
+  },
+  "chocolate_cake": {
+    "common_allergens": ["Gluten", "Dairy", "Egg", "Wheat"],
+    "may_contain": ["Nuts", "Soy"]
+  },
+  "french_fries": {
+    "common_allergens": [],
+    "may_contain": ["Gluten", "Wheat"]
+  },
+  "ice_cream": {
+    "common_allergens": ["Dairy"],
+    "may_contain": ["Egg", "Nuts", "Soy"]
+  },
+  "tacos": {
+    "common_allergens": ["Gluten", "Dairy", "Wheat"],
+    "may_contain": ["Soy"]
+  },
+  "steak": {
+    "common_allergens": [],
+    "may_contain": []
+  },
+  "fish_and_chips": {
+    "common_allergens": ["Fish", "Gluten", "Wheat"],
+    "may_contain": ["Egg"]
+  },
+  "shrimp_and_grits": {
+    "common_allergens": ["Shellfish", "Dairy"],
+    "may_contain": ["Gluten", "Wheat"]
+  },
+  "lobster_bisque": {
+    "common_allergens": ["Shellfish", "Dairy"],
+    "may_contain": ["Gluten", "Wheat"]
+  },
+  "crab_cakes": {
+    "common_allergens": ["Shellfish", "Egg", "Gluten", "Wheat"],
+    "may_contain": ["Dairy"]
+  },
+  "oysters": {
+    "common_allergens": ["Shellfish"],
+    "may_contain": []
+  },
+  "mussels": {
+    "common_allergens": ["Shellfish"],
+    "may_contain": []
+  },
+  "scallops": {
+    "common_allergens": ["Shellfish"],
+    "may_contain": []
+  },
+  "fried_calamari": {
+    "common_allergens": ["Shellfish", "Gluten", "Wheat"],
+    "may_contain": ["Egg"]
+  },
+  "sashimi": {
+    "common_allergens": ["Fish"],
+    "may_contain": []
+  },
+  "tuna_tartare": {
+    "common_allergens": ["Fish"],
+    "may_contain": ["Egg", "Soy"]
+  },
+  "cheese_plate": {
+    "common_allergens": ["Dairy"],
+    "may_contain": ["Nuts"]
+  },
+  "macaroni_and_cheese": {
+    "common_allergens": ["Gluten", "Dairy", "Wheat"],
+    "may_contain": ["Egg"]
+  },
+  "eggs_benedict": {
+    "common_allergens": ["Egg", "Dairy", "Gluten", "Wheat"],
+    "may_contain": []
+  },
+  "omelette": {
+    "common_allergens": ["Egg", "Dairy"],
+    "may_contain": []
+  },
+  "deviled_eggs": {
+    "common_allergens": ["Egg"],
+    "may_contain": ["Soy"]
+  },
+  "donuts": {
+    "common_allergens": ["Gluten", "Dairy", "Egg", "Wheat"],
+    "may_contain": ["Soy", "Nuts"]
+  },
+  "churros": {
+    "common_allergens": ["Gluten", "Wheat"],
+    "may_contain": ["Dairy", "Egg"]
+  },
+  "onion_rings": {
+    "common_allergens": ["Gluten", "Wheat"],
+    "may_contain": ["Dairy", "Egg"]
+  }
+} 

app.py

@@ -1,3 +1,4 @@
+# EatSmart Pro - Professional Version with All Features
 import streamlit as st
 from PIL import Image
 import torch
@@ -10,18 +11,26 @@ import requests
 import json
 import timm
 import numpy as np
-from huggingface_hub import hf_hub_download
-import time
 
 # Page Configuration
 st.set_page_config(
     page_title="🍽️ EatSmart Pro - AI Food Analysis",
     page_icon="🍽️",
     layout="wide",
-    initial_sidebar_state="expanded"
+    initial_sidebar_state="collapsed"  # Start with sidebar closed
 )
 
-# Custom CSS for Beautiful UI
+# Mobile menu indicator - restored from history
+st.markdown("""
+<div style="display: block; background: linear-gradient(90deg, #28a745 0%, #fd7e14 50%, #007bff 100%); 
+           padding: 8px 15px; border-radius: 8px; margin-bottom: 15px; text-align: center;">
+    <p style="color: white; margin: 0; font-size: 14px;">
+        📱 <strong>Mobile Users:</strong> Click the <strong>></strong> arrow (top-left) to set dietary preferences
+    </p>
+</div>
+""", unsafe_allow_html=True)
+
+# Professional CSS with better colors - green, orange, light blue theme
 st.markdown("""
 <style>
     .stApp {
@@ -30,12 +39,12 @@ st.markdown("""
     }
     
     .main-header {
-        background: linear-gradient(90deg, #ff6b6b 0%, #4ecdc4 50%, #45b7d1 100%);
+        background: linear-gradient(90deg, #28a745 0%, #fd7e14 50%, #007bff 100%);
         padding: 20px;
         border-radius: 15px;
         text-align: center;
         margin-bottom: 20px;
-        box-shadow: 0 8px 32px rgba(0,0,0,0.3);
+        box-shadow: 0 8px 32px rgba(0,0,0,0.1);
     }
     
     .main-header h1 {
@@ -51,45 +60,45 @@ st.markdown("""
         margin: 10px 0 0 0;
     }
     
-    .stTabs [data-baseweb="tab-list"] {
-        gap: 8px;
-        background: rgba(240,240,240,0.8);
-        border-radius: 10px;
-        padding: 5px;
-    }
-    
-    .stTabs [data-baseweb="tab"] {
-        background: rgba(255,255,255,0.9);
-        border-radius: 8px;
-        color: #333333;
-        font-weight: bold;
-        padding: 10px 20px;
+    .upload-section {
+        background: linear-gradient(135deg, #28a745 0%, #20c997 100%);
+        padding: 20px;
+        border-radius: 15px;
+        text-align: center;
+        margin-bottom: 20px;
+        color: white;
+        box-shadow: 0 4px 15px rgba(40, 167, 69, 0.3);
     }
     
-    .stTabs [aria-selected="true"] {
-        background: linear-gradient(45deg, #ff6b6b, #4ecdc4);
+    .analysis-section {
+        background: linear-gradient(135deg, #007bff 0%, #0056b3 100%);
+        padding: 20px;
+        border-radius: 15px;
+        text-align: center;
+        margin-bottom: 20px;
         color: white;
+        box-shadow: 0 4px 15px rgba(0, 123, 255, 0.3);
     }
     
     .info-card {
-        background: rgba(255,255,255,0.9);
+        background: rgba(255,255,255,0.95);
         backdrop-filter: blur(10px);
         border-radius: 15px;
         padding: 20px;
         margin: 10px 0;
         border: 1px solid rgba(0,0,0,0.1);
-        box-shadow: 0 8px 32px rgba(0,0,0,0.1);
+        box-shadow: 0 4px 20px rgba(0,0,0,0.1);
         color: #333333;
     }
     
     .metric-card {
-        background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+        background: linear-gradient(135deg, #20c997 0%, #17a2b8 100%);
         padding: 15px;
         border-radius: 10px;
         text-align: center;
         color: white;
         margin: 5px;
-        box-shadow: 0 4px 15px rgba(0,0,0,0.2);
+        box-shadow: 0 4px 15px rgba(32, 201, 151, 0.3);
     }
     
     .metric-value {
@@ -100,80 +109,105 @@ st.markdown("""
     
     .metric-label {
         font-size: 0.9rem;
-        opacity: 0.8;
+        opacity: 0.9;
     }
     
     .health-score-excellent {
-        background: linear-gradient(135deg, #56ab2f 0%, #a8e6cf 100%);
+        background: linear-gradient(135deg, #28a745 0%, #20c997 100%);
         color: white;
         padding: 15px;
         border-radius: 10px;
         text-align: center;
         font-weight: bold;
         margin: 10px 0;
+        box-shadow: 0 4px 15px rgba(40, 167, 69, 0.3);
     }
     
     .health-score-good {
-        background: linear-gradient(135deg, #f7971e 0%, #ffd200 100%);
+        background: linear-gradient(135deg, #17a2b8 0%, #20c997 100%);
         color: white;
         padding: 15px;
         border-radius: 10px;
         text-align: center;
         font-weight: bold;
         margin: 10px 0;
+        box-shadow: 0 4px 15px rgba(23, 162, 184, 0.3);
     }
     
     .health-score-poor {
-        background: linear-gradient(135deg, #ff416c 0%, #ff4b2b 100%);
+        background: linear-gradient(135deg, #dc3545 0%, #c82333 100%);
         color: white;
         padding: 15px;
         border-radius: 10px;
         text-align: center;
         font-weight: bold;
         margin: 10px 0;
-    }
-    
-    .stButton > button {
-        background: linear-gradient(45deg, #ff6b6b, #4ecdc4);
-        color: white;
-        border: none;
-        border-radius: 25px;
-        padding: 10px 20px;
-        font-weight: bold;
-        transition: all 0.3s ease;
-    }
-    
-    .stButton > button:hover {
-        transform: translateY(-2px);
-        box-shadow: 0 5px 15px rgba(0,0,0,0.3);
+        box-shadow: 0 4px 15px rgba(220, 53, 69, 0.3);
     }
     
     .allergen-alert {
-        background: linear-gradient(135deg, #ff416c 0%, #ff4b2b 100%);
+        background: linear-gradient(135deg, #dc3545 0%, #c82333 100%);
         color: white;
         padding: 15px;
         border-radius: 10px;
         margin: 10px 0;
-        border-left: 5px solid #ff0000;
+        border-left: 5px solid #a71e2a;
+        box-shadow: 0 4px 15px rgba(220, 53, 69, 0.3);
+        animation: pulse 2s infinite;
+    }
+    
+    @keyframes pulse {
+        0% { box-shadow: 0 4px 15px rgba(220, 53, 69, 0.3); }
+        50% { box-shadow: 0 4px 25px rgba(220, 53, 69, 0.6); }
+        100% { box-shadow: 0 4px 15px rgba(220, 53, 69, 0.3); }
     }
     
     .allergen-info {
-        background: linear-gradient(135deg, #4facfe 0%, #00f2fe 100%);
+        background: linear-gradient(135deg, #007bff 0%, #0056b3 100%);
         color: white;
         padding: 15px;
         border-radius: 10px;
         margin: 10px 0;
-        border-left: 5px solid #0066cc;
+        border-left: 5px solid #004085;
+        box-shadow: 0 4px 15px rgba(0, 123, 255, 0.3);
     }
     
     .recipe-section {
-        background: rgba(255,255,255,0.9);
-        border-radius: 10px;
-        padding: 15px;
+        background: rgba(255,255,255,0.95);
+        border-radius: 15px;
+        padding: 20px;
         margin: 10px 0;
-        border-left: 4px solid #4ecdc4;
+        border-left: 4px solid #28a745;
         color: #333333;
         border: 1px solid rgba(0,0,0,0.1);
+        box-shadow: 0 4px 20px rgba(0,0,0,0.1);
+    }
+    
+    .stButton > button {
+        background: linear-gradient(45deg, #28a745, #007bff);
+        color: white;
+        border: none;
+        border-radius: 25px;
+        padding: 12px 24px;
+        font-weight: bold;
+        font-size: 1.1rem;
+        transition: all 0.3s ease;
+        box-shadow: 0 4px 15px rgba(0,0,0,0.2);
+    }
+    
+    .stButton > button:hover {
+        transform: translateY(-2px);
+        box-shadow: 0 6px 20px rgba(0,0,0,0.3);
+    }
+    
+    .camera-section {
+        background: linear-gradient(135deg, #17a2b8 0%, #20c997 100%);
+        padding: 15px;
+        border-radius: 10px;
+        margin: 10px 0;
+        text-align: center;
+        color: white;
+        box-shadow: 0 4px 15px rgba(23, 162, 184, 0.3);
     }
 </style>
 """, unsafe_allow_html=True)
@@ -217,45 +251,6 @@ if 'prediction_result' not in st.session_state:
     st.session_state.prediction_result = None
 
 # Helper Functions
-def download_model_with_progress():
-    """Download model from HF Hub with progress tracking"""
-    try:
-        # Show download progress
-        progress_bar = st.progress(0)
-        status_text = st.empty()
-        
-        status_text.text("🔄 Initializing model download...")
-        progress_bar.progress(20)
-        time.sleep(0.3)
-        
-        status_text.text("📥 Downloading ConvNeXt Large model (2.3GB)...")
-        progress_bar.progress(40)
-        
-        # Download the model file
-        model_path = hf_hub_download(
-            repo_id="Lumilife/eatSmartPro-models",
-            filename="food_classifier_convnext_large_cpu_full.pth",
-            cache_dir="./models"
-        )
-        
-        progress_bar.progress(80)
-        status_text.text("✅ Model downloaded successfully!")
-        time.sleep(0.3)
-        
-        progress_bar.progress(100)
-        status_text.text("🚀 Loading model into memory...")
-        time.sleep(0.3)
-        
-        # Clear progress indicators
-        progress_bar.empty()
-        status_text.empty()
-        
-        return model_path
-        
-    except Exception as e:
-        st.error(f"❌ Failed to download model: {str(e)}")
-        return None
-
 def get_convnext_model(num_classes):
     """Creates the ConvNeXt Large model architecture"""
     print(f"🚀 Loading ConvNeXt Large model for inference...")
@@ -264,53 +259,80 @@ def get_convnext_model(num_classes):
     print(f"✅ Model loaded: {total_params:,} parameters (~{total_params * 4 / 1024**2:.1f} MB)")
     return model
 
+def get_efficientnet_model(num_classes):
+    """Creates EfficientNet-V2-S model for fallback"""
+    print(f"⚠️ Loading EfficientNet-V2-S model (fallback)...")
+    model = models.efficientnet_v2_s(weights=None)
+    num_features = model.classifier[1].in_features
+    model.classifier = nn.Sequential(
+        nn.Dropout(p=0.2),
+        nn.Linear(num_features, 256),
+        nn.ReLU(),
+        nn.Dropout(p=0.1),
+        nn.Linear(256, num_classes)
+    )
+    return model
+
 @st.cache_resource
 def load_model_resources():
-    """Load model with HF Hub download"""
+    """Load model with smart detection"""
     num_classes = len(CLASS_NAMES)
     
-    # Check if model exists locally first
-    local_model_path = "./models/food_classifier_convnext_large_cpu_full.pth"
+    # Try to load ConvNeXt Large model first
+    convnext_path = "models/food_classifier_convnext_large_cpu_full.pth"
+    efficientnet_path = "models/food101_efficientnet_best.pth"
     
-    if not os.path.exists(local_model_path):
-        st.info("🔄 First time setup: Downloading high-accuracy model...")
-        model_path = download_model_with_progress()
-        if not model_path:
-            st.error("❌ Failed to download model. Please refresh the page.")
-            return None, None
-    else:
-        model_path = local_model_path
+    model = None
+    model_info = {"name": "Unknown", "params": 0, "accuracy": "Unknown"}
     
-    try:
-        st.info("🎯 Loading ConvNeXt Large model...")
-        model = get_convnext_model(num_classes)
-        
-        # Load checkpoint
-        checkpoint = torch.load(model_path, map_location='cpu')
-        
-        # Handle different checkpoint formats
-        if isinstance(checkpoint, dict):
-            if 'model_state_dict' in checkpoint:
-                model.load_state_dict(checkpoint['model_state_dict'], strict=False)
-                model_info = {
-                    "name": "ConvNeXt Large",
-                    "params": "197M",
-                    "accuracy": f"{checkpoint.get('best_acc', 89.8):.1f}%"
-                }
+    if os.path.exists(convnext_path):
+        try:
+            print("🎯 Loading ConvNeXt Large model...")
+            model = get_convnext_model(num_classes)
+            checkpoint = torch.load(convnext_path, map_location='cpu')
+            
+            # Handle different checkpoint formats
+            if isinstance(checkpoint, dict):
+                if 'model_state_dict' in checkpoint:
+                    model.load_state_dict(checkpoint['model_state_dict'], strict=False)
+                    model_info = {
+                        "name": "ConvNeXt Large",
+                        "params": "197M",
+                        "accuracy": f"{checkpoint.get('best_acc', 89.8):.1f}%"
+                    }
+                else:
+                    model.load_state_dict(checkpoint, strict=False)
+                    model_info = {"name": "ConvNeXt Large", "params": "197M", "accuracy": "89.8%"}
             else:
                 model.load_state_dict(checkpoint, strict=False)
                 model_info = {"name": "ConvNeXt Large", "params": "197M", "accuracy": "89.8%"}
-        else:
+            
+            model.eval()
+            print("✅ ConvNeXt Large model loaded successfully!")
+            
+        except Exception as e:
+            print(f"❌ Failed to load ConvNeXt model: {e}")
+            model = None
+    
+    # Fallback to EfficientNet if ConvNeXt fails
+    if model is None and os.path.exists(efficientnet_path):
+        try:
+            print("🔄 Loading EfficientNet-V2-S model (fallback)...")
+            model = get_efficientnet_model(num_classes)
+            checkpoint = torch.load(efficientnet_path, map_location='cpu')
             model.load_state_dict(checkpoint, strict=False)
-            model_info = {"name": "ConvNeXt Large", "params": "197M", "accuracy": "89.8%"}
-        
-        model.eval()
-        st.success("✅ High-accuracy model loaded successfully!")
-        return model, model_info
-        
-    except Exception as e:
-        st.error(f"❌ Failed to load model: {str(e)}")
+            model.eval()
+            model_info = {"name": "EfficientNet-V2-S", "params": "21M", "accuracy": "85.2%"}
+            print("✅ EfficientNet model loaded successfully!")
+        except Exception as e:
+            print(f"❌ Failed to load EfficientNet model: {e}")
+            model = None
+    
+    if model is None:
+        st.error("❌ No model could be loaded. Please check model files.")
         return None, None
+    
+    return model, model_info
 
 def load_json_data(path):
     """Load JSON data with error handling"""
@@ -376,25 +398,30 @@ def get_health_score(food_name, health_data):
     return nutrition.get('health_score', 'Good')
 
 def get_allergen_info(food_name, allergen_data):
-    """Get allergen information"""
-    return allergen_data.get(food_name, {
+    """Get allergen information with enhanced user-specific alerts"""
+    allergen_info = allergen_data.get(food_name, {
         'common_allergens': [],
         'may_contain': []
     })
+    
+    return allergen_info
 
 def get_common_ingredients(food_name):
-    """Get common ingredients for a food item"""
+    """Get common ingredients for a food item with enhanced protein focus"""
     ingredients_db = {
-        'grilled_salmon': ['salmon fillet', 'olive oil', 'lemon', 'herbs', 'salt', 'pepper'],
-        'chicken_curry': ['chicken', 'curry spices', 'coconut milk', 'onions', 'garlic', 'ginger'],
-        'caesar_salad': ['romaine lettuce', 'parmesan cheese', 'croutons', 'caesar dressing'],
-        'hamburger': ['ground beef', 'burger bun', 'lettuce', 'tomato', 'onion', 'pickles'],
-        'pizza': ['pizza dough', 'tomato sauce', 'mozzarella cheese', 'various toppings'],
-        'sushi': ['sushi rice', 'nori seaweed', 'fresh fish', 'wasabi', 'soy sauce'],
-        'chocolate_cake': ['flour', 'cocoa powder', 'sugar', 'eggs', 'butter', 'vanilla'],
+        'grilled_salmon': ['salmon fillet (high protein)', 'olive oil', 'lemon', 'herbs', 'salt', 'pepper'],
+        'chicken_curry': ['chicken breast (high protein)', 'curry spices', 'coconut milk', 'onions', 'garlic', 'ginger'],
+        'caesar_salad': ['romaine lettuce', 'parmesan cheese (protein)', 'croutons', 'caesar dressing'],
+        'hamburger': ['ground beef (high protein)', 'burger bun', 'lettuce', 'tomato', 'onion', 'pickles'],
+        'pizza': ['pizza dough', 'tomato sauce', 'mozzarella cheese (protein)', 'various toppings'],
+        'sushi': ['sushi rice', 'nori seaweed', 'fresh fish (high protein)', 'wasabi', 'soy sauce'],
+        'chocolate_cake': ['flour', 'cocoa powder', 'sugar', 'eggs (protein)', 'butter', 'vanilla'],
         'french_fries': ['potatoes', 'oil for frying', 'salt'],
-        'ice_cream': ['milk', 'cream', 'sugar', 'eggs', 'flavorings'],
-        'tacos': ['tortillas', 'meat or beans', 'lettuce', 'tomatoes', 'cheese', 'salsa']
+        'ice_cream': ['milk (protein)', 'cream', 'sugar', 'eggs (protein)', 'flavorings'],
+        'tacos': ['tortillas', 'meat or beans (protein)', 'lettuce', 'tomatoes', 'cheese (protein)', 'salsa'],
+        'steak': ['beef steak (very high protein)', 'seasonings', 'cooking oil'],
+        'eggs_benedict': ['eggs (high protein)', 'english muffin', 'canadian bacon (protein)', 'hollandaise sauce'],
+        'greek_salad': ['lettuce', 'tomatoes', 'feta cheese (protein)', 'olives', 'olive oil', 'herbs']
     }
     
     return ingredients_db.get(food_name, [
@@ -405,8 +432,7 @@ def get_common_ingredients(food_name):
     ])
 
 def generate_recipe(food_name):
-    """Generate personalized recipe using free Hugging Face models"""
-    # For now, use fallback recipe system since HF inference can be unreliable
+    """Generate personalized recipe using built-in database"""
     food_display = food_name.replace('_', ' ').title()
     
     dietary_restrictions = ""
@@ -424,63 +450,75 @@ def generate_recipe(food_name):
     return generate_fallback_recipe(food_display, dietary_restrictions, allergen_restrictions, trans_fat_note)
 
 def generate_fallback_recipe(food_display, dietary_restrictions, allergen_restrictions, trans_fat_note):
-    """Generate a structured fallback recipe when AI models are unavailable"""
+    """Generate a structured recipe with professional formatting"""
     
-    # Basic recipes database for common foods
+    # Enhanced recipes database with more variety
     recipe_templates = {
         'grilled_salmon': {
-            'ingredients': ['4 salmon fillets', '2 tbsp olive oil', '1 lemon (juiced)', 'salt and pepper', 'fresh herbs (dill or parsley)'],
-            'instructions': ['Preheat grill to medium-high', 'Brush salmon with olive oil', 'Season with salt, pepper, and herbs', 'Grill 4-5 minutes per side', 'Drizzle with lemon juice before serving'],
+            'ingredients': ['4 salmon fillets (6 oz each)', '2 tbsp extra virgin olive oil', '1 lemon (juiced)', 'fresh dill or parsley', 'sea salt and black pepper', 'garlic powder'],
+            'instructions': ['Preheat grill to medium-high heat', 'Pat salmon dry and brush with olive oil', 'Season generously with salt, pepper, and garlic powder', 'Grill 4-5 minutes per side until flakes easily', 'Garnish with fresh herbs and lemon juice'],
             'prep_time': '15 minutes',
-            'servings': '4'
+            'servings': '4',
+            'protein_content': 'Very High (35g per serving)'
         },
         'chicken_curry': {
-            'ingredients': ['1 lb chicken breast (cubed)', '1 onion (diced)', '2 cloves garlic', '1 tbsp curry powder', '1 can coconut milk', '1 cup vegetables'],
-            'instructions': ['Sauté onion and garlic', 'Add chicken and curry powder', 'Pour in coconut milk', 'Add vegetables', 'Simmer 20 minutes until tender'],
+            'ingredients': ['1 lb chicken breast (cubed)', '1 large onion (diced)', '3 cloves garlic (minced)', '1 tbsp curry powder', '1 can coconut milk', '1 cup mixed vegetables', 'ginger', 'cilantro'],
+            'instructions': ['Heat oil in large pan over medium heat', 'Sauté onion and garlic until fragrant', 'Add chicken and curry powder, cook until browned', 'Pour in coconut milk and simmer', 'Add vegetables and cook 15-20 minutes until tender'],
             'prep_time': '30 minutes',
-            'servings': '4'
+            'servings': '4',
+            'protein_content': 'High (28g per serving)'
         },
         'caesar_salad': {
-            'ingredients': ['1 head romaine lettuce', '1/4 cup parmesan cheese', '2 tbsp olive oil', '1 tbsp lemon juice', 'croutons', 'black pepper'],
-            'instructions': ['Wash and chop lettuce', 'Make dressing with oil and lemon', 'Toss lettuce with dressing', 'Top with cheese and croutons', 'Season with pepper'],
+            'ingredients': ['1 large head romaine lettuce', '1/3 cup parmesan cheese (grated)', '2 tbsp olive oil', '1 tbsp lemon juice', 'whole grain croutons', 'black pepper', 'caesar dressing'],
+            'instructions': ['Wash and chop lettuce into bite-sized pieces', 'Make dressing with oil, lemon, and seasonings', 'Toss lettuce with dressing until well coated', 'Top with parmesan cheese and croutons', 'Season with fresh black pepper'],
             'prep_time': '10 minutes',
-            'servings': '2'
+            'servings': '2-3',
+            'protein_content': 'Moderate (8g per serving)'
         },
         'hamburger': {
-            'ingredients': ['1 lb ground beef', '4 burger buns', 'lettuce', 'tomato', 'onion', 'cheese', 'condiments'],
-            'instructions': ['Form beef into patties', 'Season with salt and pepper', 'Grill or pan-fry 4-5 minutes per side', 'Toast buns lightly', 'Assemble with toppings'],
+            'ingredients': ['1 lb lean ground beef (80/20)', '4 whole grain burger buns', 'lettuce leaves', '2 tomatoes (sliced)', '1 onion (sliced)', 'pickles', 'low-fat cheese (optional)'],
+            'instructions': ['Form beef into 4 equal patties', 'Season with salt and pepper', 'Grill or pan-cook 4-5 minutes per side', 'Toast buns lightly on grill', 'Assemble with fresh vegetables and condiments'],
             'prep_time': '20 minutes',
-            'servings': '4'
+            'servings': '4',
+            'protein_content': 'Very High (25g per serving)'
         },
         'pizza': {
-            'ingredients': ['pizza dough', 'tomato sauce', '2 cups mozzarella cheese', 'toppings of choice', 'olive oil', 'herbs'],
-            'instructions': ['Preheat oven to 450°F', 'Roll out dough', 'Spread sauce evenly', 'Add cheese and toppings', 'Bake 12-15 minutes until golden'],
+            'ingredients': ['whole wheat pizza dough', 'tomato sauce (low sodium)', '1.5 cups mozzarella cheese', 'vegetables of choice', 'olive oil', 'Italian herbs', 'fresh basil'],
+            'instructions': ['Preheat oven to 450°F (230°C)', 'Roll out dough on floured surface', 'Spread sauce evenly, leaving border for crust', 'Add cheese and favorite toppings', 'Bake 12-15 minutes until golden and bubbly'],
             'prep_time': '25 minutes',
-            'servings': '4'
+            'servings': '4',
+            'protein_content': 'Moderate (15g per serving)'
         }
     }
     
     # Get template or create generic one
     food_key = food_display.lower().replace(' ', '_')
     template = recipe_templates.get(food_key, {
-        'ingredients': [f'Main ingredient for {food_display}', 'Seasonings and spices', 'Healthy cooking oil', 'Fresh vegetables', 'Herbs for flavor'],
-        'instructions': ['Prepare all ingredients', 'Use healthy cooking methods', 'Season appropriately', 'Cook until done', 'Serve with vegetables'],
+        'ingredients': [f'Main protein source for {food_display}', 'Fresh vegetables', 'Healthy seasonings', 'Quality cooking oil', 'Herbs and spices'],
+        'instructions': ['Prepare all ingredients fresh', 'Use healthy cooking methods (grill, bake, steam)', 'Season with herbs instead of excess salt', 'Cook until properly done', 'Serve with colorful vegetables'],
         'prep_time': '20-30 minutes',
-        'servings': '2-4'
+        'servings': '2-4',
+        'protein_content': 'Varies by ingredients'
     })
     
     # Apply dietary modifications
     modifications = []
     if 'vegan' in dietary_restrictions.lower():
-        modifications.append("🌱 Use plant-based ingredients only")
+        modifications.append("🌱 Replace animal proteins with plant-based alternatives (tofu, tempeh, legumes)")
+    if 'vegetarian' in dietary_restrictions.lower():
+        modifications.append("🥬 Use vegetarian protein sources (eggs, dairy, plant proteins)")
     if 'keto' in dietary_restrictions.lower():
-        modifications.append("🥑 Keep carbs under 5g per serving")
+        modifications.append("🥑 Keep carbs under 5g per serving, increase healthy fats")
+    if 'high-protein' in dietary_restrictions.lower():
+        modifications.append("💪 Add extra protein sources to reach 25g+ per serving")
     if 'gluten' in allergen_restrictions.lower():
-        modifications.append("⚠️ Use gluten-free alternatives")
+        modifications.append("⚠️ Use certified gluten-free alternatives for all grains")
+    if 'dairy' in allergen_restrictions.lower():
+        modifications.append("🥛 Replace dairy with plant-based alternatives (almond, oat milk)")
     if trans_fat_note:
-        modifications.append("💚 Use healthy oils (olive, avocado, coconut)")
+        modifications.append("💚 Use only healthy oils: olive, avocado, or coconut oil")
     
-    recipe = f"""**🍽️ Healthy {food_display} Recipe**
+    recipe = f"""**🍽️ Professional {food_display} Recipe**
 
 **Ingredients:**
 {chr(10).join(f'• {ingredient}' for ingredient in template['ingredients'])}
@@ -488,20 +526,244 @@ def generate_fallback_recipe(food_display, dietary_restrictions, allergen_restri
 **Instructions:**
 {chr(10).join(f'{i+1}. {instruction}' for i, instruction in enumerate(template['instructions']))}
 
-**Chef's Tips:**
-• Use fresh, high-quality ingredients for best flavor
-• Adjust seasonings to your taste preferences
-• Include colorful vegetables for added nutrition
-• Control portion sizes for balanced eating
+**Nutritional Highlights:**
+• **Protein Content:** {template['protein_content']}
+• **Prep Time:** {template['prep_time']}
+• **Servings:** {template['servings']}
 
-**Prep Time:** {template['prep_time']}
-**Servings:** {template['servings']}"""
+**Chef's Professional Tips:**
+• Use the freshest ingredients available for optimal flavor
+• Control portion sizes for balanced nutrition
+• Include a variety of colorful vegetables for micronutrients
+• Season gradually and taste as you go
+• Let proteins rest before serving for better texture"""
 
     if modifications:
         recipe += f"\n\n**🎯 Your Personalized Modifications:**\n{chr(10).join(f'• {mod}' for mod in modifications)}"
     
-    recipe += "\n\n*💡 Recipe generated using built-in healthy cooking database - completely free!*"
+    recipe += "\n\n*💡 Recipe crafted using professional culinary database - completely free and personalized!*"
+    
+    return recipe
+
+def generate_multiple_recipes(food_name):
+    """Generate 3 different recipe variations with food images"""
+    food_display = food_name.replace('_', ' ').title()
+    
+    # Initialize recipe count in session state
+    if 'recipe_count' not in st.session_state:
+        st.session_state.recipe_count = 0
+    if 'generated_recipes' not in st.session_state:
+        st.session_state.generated_recipes = []
+    
+    # Food images URLs - FIXED with correct food-specific images
+    food_images = {
+        'grilled_salmon': [
+            'https://images.unsplash.com/photo-1467003909585-2f8a72700288?w=300&h=200&fit=crop&auto=format',
+            'https://images.unsplash.com/photo-1519708227418-c8fd9a32b7a2?w=300&h=200&fit=crop&auto=format',
+            'https://images.unsplash.com/photo-1485704686097-ed47f7263ca4?w=300&h=200&fit=crop&auto=format',
+            'https://images.unsplash.com/photo-1544943910-4c1dc44aab44?w=300&h=200&fit=crop&auto=format',
+            'https://images.unsplash.com/photo-1559847844-d721426d6edc?w=300&h=200&fit=crop&auto=format',
+            'https://images.unsplash.com/photo-1553979459-d2229ba7433a?w=300&h=200&fit=crop&auto=format',
+            'https://images.unsplash.com/photo-1478145046317-39f10e56b5e9?w=300&h=200&fit=crop&auto=format',
+            'https://images.unsplash.com/photo-1535140728325-781d5ecd3e95?w=300&h=200&fit=crop&auto=format',
+            'https://images.unsplash.com/photo-1546833999-b9f581a1996d?w=300&h=200&fit=crop&auto=format'
+        ],
+        'steak': [
+            'https://images.unsplash.com/photo-1546833999-b9f581a1996d?w=300&h=200&fit=crop&auto=format&q=80',
+            'https://images.unsplash.com/photo-1558030006-450675393462?w=300&h=200&fit=crop&auto=format&q=80',
+            'https://images.unsplash.com/photo-1544025162-d76694265947?w=300&h=200&fit=crop&auto=format&q=80',
+            'https://images.unsplash.com/photo-1504973960431-1c467e159aa4?w=300&h=200&fit=crop&auto=format&q=80',
+            'https://images.unsplash.com/photo-1615937691194-97ddb5266e4a?w=300&h=200&fit=crop&auto=format&q=80',
+            'https://images.unsplash.com/photo-1603360946369-dc9bb6258143?w=300&h=200&fit=crop&auto=format&q=80',
+            'https://images.unsplash.com/photo-1529692236671-f1f6cf9683ba?w=300&h=200&fit=crop&auto=format&q=80',
+            'https://images.unsplash.com/photo-1551782450-17144efb9c50?w=300&h=200&fit=crop&auto=format&q=80',
+            'https://images.unsplash.com/photo-1572802419224-296b0aeee0d9?w=300&h=200&fit=crop&auto=format&q=80'
+        ],
+        'pizza': [
+            'https://images.unsplash.com/photo-1513104890138-7c749659a591?w=300&h=200&fit=crop&auto=format',
+            'https://images.unsplash.com/photo-1565299624946-b28f40a0ca4b?w=300&h=200&fit=crop&auto=format',
+            'https://images.unsplash.com/photo-1571407970349-bc81e7e96d47?w=300&h=200&fit=crop&auto=format',
+            'https://images.unsplash.com/photo-1574071318508-1cdbab80d002?w=300&h=200&fit=crop&auto=format',
+            'https://images.unsplash.com/photo-1506354666786-959d6d497f1a?w=300&h=200&fit=crop&auto=format',
+            'https://images.unsplash.com/photo-1593560708920-61dd98c46a4e?w=300&h=200&fit=crop&auto=format',
+            'https://images.unsplash.com/photo-1628840042765-356cda07504e?w=300&h=200&fit=crop&auto=format',
+            'https://images.unsplash.com/photo-1585238342024-78d387f4a707?w=300&h=200&fit=crop&auto=format',
+            'https://images.unsplash.com/photo-1571407970349-bc81e7e96d47?w=300&h=200&fit=crop&auto=format'
+        ],
+        'chicken_curry': [
+            'https://images.unsplash.com/photo-1565557623262-b51c2513a641?w=300&h=200&fit=crop&auto=format',
+            'https://images.unsplash.com/photo-1574484284002-952d92456975?w=300&h=200&fit=crop&auto=format',
+            'https://images.unsplash.com/photo-1588166524941-3bf61a9c41db?w=300&h=200&fit=crop&auto=format',
+            'https://images.unsplash.com/photo-1631452180539-96aca7d48617?w=300&h=200&fit=crop&auto=format',
+            'https://images.unsplash.com/photo-1565299585323-38174c5f1b8b?w=300&h=200&fit=crop&auto=format',
+            'https://images.unsplash.com/photo-1603894584373-5ac82b2ae398?w=300&h=200&fit=crop&auto=format',
+            'https://images.unsplash.com/photo-1627662168223-7df99068099a?w=300&h=200&fit=crop&auto=format',
+            'https://images.unsplash.com/photo-1574484284002-952d92456975?w=300&h=200&fit=crop&auto=format',
+            'https://images.unsplash.com/photo-1588166524941-3bf61a9c41db?w=300&h=200&fit=crop&auto=format'
+        ],
+        'hamburger': [
+            'https://images.unsplash.com/photo-1568901346375-23c9450c58cd?w=300&h=200&fit=crop&auto=format',
+            'https://images.unsplash.com/photo-1550547660-d9450f859349?w=300&h=200&fit=crop&auto=format',
+            'https://images.unsplash.com/photo-1571091718767-18b5b1457add?w=300&h=200&fit=crop&auto=format',
+            'https://images.unsplash.com/photo-1553979459-d2229ba7433a?w=300&h=200&fit=crop&auto=format',
+            'https://images.unsplash.com/photo-1572802419224-296b0aeee0d9?w=300&h=200&fit=crop&auto=format',
+            'https://images.unsplash.com/photo-1594212699903-ec8a3eca50f5?w=300&h=200&fit=crop&auto=format',
+            'https://images.unsplash.com/photo-1586816001966-79b736744398?w=300&h=200&fit=crop&auto=format',
+            'https://images.unsplash.com/photo-1551782450-17144efb9c50?w=300&h=200&fit=crop&auto=format',
+            'https://images.unsplash.com/photo-1565299624946-b28f40a0ca4b?w=300&h=200&fit=crop&auto=format'
+        ],
+        'default': [
+            'https://images.unsplash.com/photo-1546793665-c74683f339c1?w=300&h=200&fit=crop&auto=format',
+            'https://images.unsplash.com/photo-1565299624946-b28f40a0ca4b?w=300&h=200&fit=crop&auto=format',
+            'https://images.unsplash.com/photo-1504674900247-0877df9cc836?w=300&h=200&fit=crop&auto=format',
+            'https://images.unsplash.com/photo-1555939594-58d7cb561ad1?w=300&h=200&fit=crop&auto=format',
+            'https://images.unsplash.com/photo-1567620905732-2d1ec7ab7445?w=300&h=200&fit=crop&auto=format',
+            'https://images.unsplash.com/photo-1482049016688-2d3e1b311543?w=300&h=200&fit=crop&auto=format',
+            'https://images.unsplash.com/photo-1540189549336-e6e99c3679fe?w=300&h=200&fit=crop&auto=format',
+            'https://images.unsplash.com/photo-1559847844-d721426d6edc?w=300&h=200&fit=crop&auto=format',
+            'https://images.unsplash.com/photo-1565299624946-b28f40a0ca4b?w=300&h=200&fit=crop&auto=format'
+        ]
+    }
+    
+    # Get images for this food or use default
+    images = food_images.get(food_name, food_images['default'])
+    
+    # Generate recipe styles based on current count
+    recipe_styles = ['healthy', 'quick', 'gourmet', 'traditional', 'fusion', 'low-carb', 'protein-rich', 'vegetarian', 'spicy']
+    
+    # Generate 3 different recipe styles
+    recipes = []
+    start_idx = st.session_state.recipe_count
+    
+    for i in range(3):
+        style_idx = (start_idx + i) % len(recipe_styles)
+        style = recipe_styles[style_idx]
+        image_idx = (start_idx + i) % len(images)
+        
+        recipes.append({
+            'title': f'{style.title()} {food_display}',
+            'image_url': images[image_idx],
+            'recipe': generate_recipe_variation(food_display, style)
+        })
+    
+    # Update recipe count
+    st.session_state.recipe_count += 3
+    
+    return recipes
+
+def generate_recipe_variation(food_display, style):
+    """Generate a recipe variation based on style"""
     
+    dietary_restrictions = ""
+    if st.session_state.dietary_preferences:
+        dietary_restrictions = f"Make it {', '.join(st.session_state.dietary_preferences).lower()}. "
+    
+    allergen_restrictions = ""
+    if st.session_state.user_allergens:
+        allergen_restrictions = f"Avoid using {', '.join(st.session_state.user_allergens).lower()}. "
+    
+    trans_fat_note = ""
+    if st.session_state.avoid_trans_fat:
+        trans_fat_note = "Use only healthy oils and avoid trans fats. "
+    
+    # Expanded style-specific modifications
+    style_modifications = {
+        'healthy': {
+            'prefix': '🥗 **HEALTHY VERSION**',
+            'cooking_methods': ['grilled', 'baked', 'steamed', 'air-fried'],
+            'ingredients_focus': 'organic and fresh ingredients',
+            'special_notes': 'Low sodium, high fiber, nutrient-dense preparation',
+            'prep_time': 25,
+            'difficulty': 2
+        },
+        'quick': {
+            'prefix': '⚡ **QUICK & EASY VERSION**',
+            'cooking_methods': ['pan-seared', 'stir-fried', 'microwaved', 'one-pot'],
+            'ingredients_focus': 'simple and accessible ingredients',
+            'special_notes': 'Ready in 15-20 minutes, minimal prep time',
+            'prep_time': 15,
+            'difficulty': 1
+        },
+        'gourmet': {
+            'prefix': '🌟 **GOURMET VERSION**',
+            'cooking_methods': ['sous-vide', 'braised', 'roasted', 'flambéed'],
+            'ingredients_focus': 'premium and artisanal ingredients',
+            'special_notes': 'Restaurant-quality presentation and techniques',
+            'prep_time': 45,
+            'difficulty': 4
+        },
+        'traditional': {
+            'prefix': '🏛️ **TRADITIONAL VERSION**',
+            'cooking_methods': ['slow-cooked', 'braised', 'roasted', 'simmered'],
+            'ingredients_focus': 'classic and time-tested ingredients',
+            'special_notes': 'Authentic preparation methods passed down through generations',
+            'prep_time': 60,
+            'difficulty': 3
+        },
+        'fusion': {
+            'prefix': '🌍 **FUSION VERSION**',
+            'cooking_methods': ['stir-fried', 'grilled', 'pan-seared', 'wok-tossed'],
+            'ingredients_focus': 'international spices and modern techniques',
+            'special_notes': 'Creative blend of culinary traditions and flavors',
+            'prep_time': 30,
+            'difficulty': 3
+        },
+        'low-carb': {
+            'prefix': '🥑 **LOW-CARB VERSION**',
+            'cooking_methods': ['grilled', 'sautéed', 'roasted', 'steamed'],
+            'ingredients_focus': 'high-protein, low-carbohydrate ingredients',
+            'special_notes': 'Under 10g carbs per serving, keto-friendly',
+            'prep_time': 20,
+            'difficulty': 2
+        },
+        'protein-rich': {
+            'prefix': '💪 **HIGH-PROTEIN VERSION**',
+            'cooking_methods': ['grilled', 'baked', 'pan-seared', 'broiled'],
+            'ingredients_focus': 'lean proteins and muscle-building nutrients',
+            'special_notes': '25g+ protein per serving, perfect for fitness goals',
+            'prep_time': 25,
+            'difficulty': 2
+        },
+        'vegetarian': {
+            'prefix': '🌱 **VEGETARIAN VERSION**',
+            'cooking_methods': ['roasted', 'sautéed', 'grilled', 'steamed'],
+            'ingredients_focus': 'plant-based proteins and fresh vegetables',
+            'special_notes': 'No meat, rich in plant proteins and nutrients',
+            'prep_time': 30,
+            'difficulty': 2
+        },
+        'spicy': {
+            'prefix': '🌶️ **SPICY VERSION**',
+            'cooking_methods': ['stir-fried', 'grilled', 'blackened', 'seared'],
+            'ingredients_focus': 'hot peppers, spices, and bold flavors',
+            'special_notes': 'Heat level: Medium to Hot, full of flavor',
+            'prep_time': 20,
+            'difficulty': 2
+        }
+    }
+    
+    style_info = style_modifications.get(style, style_modifications['healthy'])
+    
+    recipe = f"""{style_info['prefix']}
+
+**Cooking Method:** {', '.join(style_info['cooking_methods']).title()}
+**Focus:** {style_info['ingredients_focus'].title()}
+
+**Key Features:**
+• {style_info['special_notes']}
+• {dietary_restrictions.strip() if dietary_restrictions else 'Customizable to your dietary needs'}
+• {allergen_restrictions.strip() if allergen_restrictions else 'Allergen-conscious preparation'}
+• {trans_fat_note.strip() if trans_fat_note else 'Heart-healthy cooking methods'}
+
+**Professional Tips:**
+• Use high-quality, fresh ingredients for best results
+• Season gradually and taste as you cook
+• Control portion sizes for balanced nutrition
+• Pair with colorful vegetables for complete nutrition
+
+**Prep Time:** {style_info['prep_time']} minutes
+**Difficulty:** {style_info['difficulty']}/5 stars"""
+
     return recipe
 
 # Main App
@@ -510,7 +772,7 @@ def main():
     st.markdown("""
     <div class="main-header">
         <h1>🍽️ EatSmart Pro</h1>
-        <p>AI-Powered Food Analysis & Healthy Living Assistant</p>
+        <p>🌟 Your AI-Powered Nutrition Assistant 🌟</p>
     </div>
     """, unsafe_allow_html=True)
     
@@ -519,62 +781,82 @@ def main():
     health_data, allergen_data = load_data()
     
     if not model:
-        st.error("❌ Failed to load AI model. Please refresh the page.")
+        st.error("❌ Failed to load AI model. Please check the setup.")
         return
     
-    # Model status
-    st.success(f"🎯 Using {model_info['name']} model ({model_info['params']} parameters, {model_info['accuracy']} accuracy)")
+    # Model status with professional styling
+    if model_info["name"] == "ConvNeXt Large":
+        st.success(f"🎯 **HIGH ACCURACY MODEL ACTIVE** | {model_info['name']} ({model_info['params']} parameters, {model_info['accuracy']} accuracy)")
+    else:
+        st.warning(f"⚠️ Using {model_info['name']} model ({model_info['params']} parameters, {model_info['accuracy']} accuracy)")
     
-    # Sidebar - User Preferences
+    # Professional Sidebar - Enhanced from chat history
     with st.sidebar:
-        st.markdown("## 👤 Your Preferences")
+        st.markdown("""
+        <div style="text-align: center; padding: 15px; background: linear-gradient(135deg, #28a745 0%, #007bff 100%); border-radius: 10px; margin-bottom: 20px;">
+            <h3 style="color: white; margin: 0;">⚙️ Your Preferences</h3>
+            <p style="color: #f8f9fa; margin: 5px 0; font-size: 0.9em;">Personalize your analysis</p>
+        </div>
+        """, unsafe_allow_html=True)
         
-        # Allergen preferences
-        st.markdown("### ⚠️ Allergen Alerts")
-        allergen_options = [
-            "Gluten", "Dairy", "Egg", "Fish", "Shellfish", 
-            "Nuts", "Peanuts", "Soy", "Sesame"
-        ]
+        # Allergen preferences with enhanced UI from history
+        st.markdown("### 🚨 Allergen Alerts")
+        st.markdown("*Select allergens you want to be warned about:*")
         
-        st.session_state.user_allergens = st.multiselect(
-            "Select allergens to avoid:",
-            allergen_options,
-            default=st.session_state.user_allergens,
-            help="Get alerts when these allergens are detected"
-        )
+        allergen_options = ["Gluten", "Dairy", "Egg", "Fish", "Shellfish", "Nuts", "Peanuts", "Soy", "Sesame", "Wheat"]
         
-        # Dietary preferences
-        st.markdown("### 🥗 Dietary Preferences")
-        dietary_options = [
-            "Vegetarian", "Vegan", "Keto", "Low-Carb", "High-Protein",
-            "Mediterranean", "Paleo", "Gluten-Free", "Dairy-Free", "Low-Sodium"
-        ]
-        
-        st.session_state.dietary_preferences = st.multiselect(
-            "Select your dietary preferences:",
-            dietary_options,
-            default=st.session_state.dietary_preferences,
-            help="Personalize recipes and recommendations"
-        )
+        # Enhanced allergen selection from chat history
+        for allergen in allergen_options:
+            if st.checkbox(f"🔴 {allergen}", key=f"allergen_{allergen}", 
+                          value=allergen in st.session_state.user_allergens):
+                if allergen not in st.session_state.user_allergens:
+                    st.session_state.user_allergens.append(allergen)
+            else:
+                if allergen in st.session_state.user_allergens:
+                    st.session_state.user_allergens.remove(allergen)
         
         # Trans fat settings
         st.markdown("### 🧪 Trans Fat Settings")
         st.session_state.avoid_trans_fat = st.checkbox(
-            "Alert me about trans fats",
+            "⚠️ Alert me about trans fats", 
             value=st.session_state.avoid_trans_fat,
-            help="Get warnings about potentially harmful trans fats"
+            help="Get warnings about foods that may contain trans fats"
         )
         
-        # App info
+        # Enhanced dietary preferences from history
+        st.markdown("### 🌱 Dietary Preferences")
+        dietary_options = ["Vegetarian", "Vegan", "Keto", "Low-Carb", "High-Protein", "Mediterranean", "Paleo", "Gluten-Free", "Dairy-Free", "Low-Sodium"]
+        
+        for diet in dietary_options:
+            if st.checkbox(f"🥬 {diet}", key=f"diet_{diet}", 
+                          value=diet in st.session_state.dietary_preferences):
+                if diet not in st.session_state.dietary_preferences:
+                    st.session_state.dietary_preferences.append(diet)
+            else:
+                if diet in st.session_state.dietary_preferences:
+                    st.session_state.dietary_preferences.remove(diet)
+        
+        # Active preferences summary from history
+        if st.session_state.user_allergens or st.session_state.dietary_preferences or st.session_state.avoid_trans_fat:
+            st.markdown("---")
+            st.markdown("### 📋 Active Preferences")
+            if st.session_state.user_allergens:
+                st.markdown(f"🚨 **Allergen Alerts:** {', '.join(st.session_state.user_allergens)}")
+            if st.session_state.dietary_preferences:
+                st.markdown(f"🌱 **Diet:** {', '.join(st.session_state.dietary_preferences)}")
+            if st.session_state.avoid_trans_fat:
+                st.markdown("🧪 **Trans Fat Alerts:** Enabled")
+        
+        # Professional features list
         st.markdown("---")
-        st.markdown("### 🚀 Features")
+        st.markdown("### 🚀 Professional Features")
         st.markdown("""
         ✅ **High-Accuracy AI Recognition**  
         ✅ **Comprehensive Nutrition Analysis**  
         ✅ **Personalized Allergen Alerts**  
-        ✅ **AI-Generated Healthy Recipes**  
+        ✅ **Professional Recipe Generation**  
         ✅ **Trans Fat Detection**  
-        ✅ **Ingredient Analysis**  
+        ✅ **Protein Content Analysis**  
         ✅ **Health Score Assessment**
         """)
     
@@ -582,47 +864,47 @@ def main():
     col1, col2 = st.columns([1, 1])
     
     with col1:
+        # Professional upload section
         st.markdown("""
-        <div style="text-align: center; padding: 15px; background: linear-gradient(135deg, #ff6b6b 0%, #4ecdc4 100%); border-radius: 10px; margin-bottom: 20px;">
-            <h3 style="color: white; margin: 0;">📸 Upload Food Image</h3>
-            <p style="color: #f0f0f0; margin: 5px 0; font-size: 0.9em;">Take a photo or upload from gallery</p>
+        <div class="upload-section">
+            <h3 style="margin: 0;">📸 Upload Food Image</h3>
+            <p style="margin: 5px 0; font-size: 0.9em;">Choose your preferred method below</p>
         </div>
         """, unsafe_allow_html=True)
         
-        # Image input options
-        input_method = st.radio(
-            "Choose input method:",
-            ["📁 Upload from device", "📷 Take photo with camera"],
-            horizontal=True
+        # File upload - no radio buttons as requested
+        st.markdown("#### 📁 Browse Files")
+        uploaded_file = st.file_uploader(
+            "Choose a food image from your device...",
+            type=["jpg", "jpeg", "png"],
+            help="Upload a clear image of your food for best results"
         )
+        if uploaded_file:
+            try:
+                uploaded_image = uploaded_file.getvalue()
+                st.session_state.image_buffer = uploaded_image
+                st.success("✅ Image uploaded successfully!")
+            except Exception as e:
+                st.error(f"❌ Error uploading image: {str(e)}")
+                st.info("Please try a different image format (JPG, JPEG, or PNG).")
         
-        uploaded_image = None
-        
-        if input_method == "📁 Upload from device":
-            uploaded_file = st.file_uploader(
-                "Choose a food image...",
-                type=["jpg", "jpeg", "png"],
-                help="Upload a clear image of your food for best results"
-            )
-            if uploaded_file:
-                try:
-                    uploaded_image = uploaded_file.getvalue()
-                    st.session_state.image_buffer = uploaded_image
-                    st.success("✅ Image uploaded successfully!")
-                except Exception as e:
-                    st.error(f"❌ Error uploading image: {str(e)}")
-                    st.info("Please try a different image format (JPG, JPEG, or PNG).")
+        # Camera functionality - restored from history
+        st.markdown("#### 📷 Take Photo")
+        st.markdown("""
+        <div class="camera-section">
+            <p style="margin: 5px 0;">Use your device camera to capture food</p>
+        </div>
+        """, unsafe_allow_html=True)
         
-        elif input_method == "📷 Take photo with camera":
-            camera_photo = st.camera_input("Take a picture of your food")
-            if camera_photo:
-                try:
-                    uploaded_image = camera_photo.getvalue()
-                    st.session_state.image_buffer = uploaded_image
-                    st.success("✅ Photo captured successfully!")
-                except Exception as e:
-                    st.error(f"❌ Error capturing photo: {str(e)}")
-                    st.info("Please try taking the photo again.")
+        camera_photo = st.camera_input("Take a picture of your food")
+        if camera_photo:
+            try:
+                uploaded_image = camera_photo.getvalue()
+                st.session_state.image_buffer = uploaded_image
+                st.success("✅ Photo captured successfully!")
+            except Exception as e:
+                st.error(f"❌ Error capturing photo: {str(e)}")
+                st.info("Please try taking the photo again.")
         
         # Display uploaded image and auto-analyze
         if st.session_state.image_buffer:
@@ -645,7 +927,7 @@ def main():
                             st.session_state.prediction_result = predictions
                             st.session_state.last_image_buffer = st.session_state.image_buffer
                             st.session_state.last_analyzed_buffer = st.session_state.image_buffer
-                            st.success("✅ Analysis complete! Check the results on the right →")
+                            st.success("✅ Analysis complete! Ready for checking")
                         except Exception as e:
                             st.error(f"❌ Error analyzing image: {str(e)}")
                             st.info("Please try uploading a different image or refresh the page.")
@@ -655,23 +937,24 @@ def main():
                 st.info("The uploaded file may be corrupted. Please try uploading again.")
     
     with col2:
+        # Professional analysis section
         st.markdown("""
-        <div style="text-align: center; padding: 15px; background: linear-gradient(135deg, #00b894 0%, #00a085 100%); border-radius: 10px; margin-bottom: 20px;">
-            <h3 style="color: white; margin: 0;">🔬 Smart Analysis & Recipes</h3>
-            <p style="color: #ddd; margin: 5px 0; font-size: 0.9em;">AI-powered nutrition insights</p>
+        <div class="analysis-section">
+            <h3 style="margin: 0;">🔬 Smart Analysis & Insights</h3>
+            <p style="margin: 5px 0; font-size: 0.9em;">AI-powered nutrition analysis</p>
         </div>
         """, unsafe_allow_html=True)
         
         # Show instruction if no image uploaded
         if not st.session_state.image_buffer:
-            st.info("👆 Upload an image above to start the analysis!")
+            st.info("👆 Upload an image or take a photo above to start the analysis!")
         
         # Display results
         if st.session_state.prediction_result and st.session_state.last_image_buffer == st.session_state.image_buffer:
             predictions = st.session_state.prediction_result
             top_prediction = predictions[0]
             
-            # Main prediction
+            # Main prediction with professional styling
             st.markdown(f"""
             <div class="info-card">
                 <h3>🎯 Food Identified</h3>
@@ -686,16 +969,16 @@ def main():
                 for pred in predictions[1:]:
                     st.write(f"• {pred['display_name']} ({pred['confidence']:.1f}%)")
             
-            # Tabs for detailed analysis
-            tab1, tab2, tab3 = st.tabs(["🏥 Health Info", "⚠️ Allergen Alerts", "👨‍🍳 Smart Recipes"])
+            # Professional tabs for detailed analysis
+            tab1, tab2, tab3 = st.tabs(["🏥 Health Analysis", "⚠️ Allergen Alerts", "👨‍🍳 Professional Recipes"])
             
             with tab1:
-                # Health information
+                # Enhanced health information
                 food_name = top_prediction['class']
                 nutrition = get_nutrition_info(food_name, health_data)
                 health_score = get_health_score(food_name, health_data)
                 
-                # Health score
+                # Professional health score
                 score_class = f"health-score-{health_score.lower()}"
                 st.markdown(f"""
                 <div class="{score_class}">
@@ -703,7 +986,7 @@ def main():
                 </div>
                 """, unsafe_allow_html=True)
                 
-                # Nutrition metrics
+                # Professional nutrition metrics
                 col1, col2, col3, col4 = st.columns(4)
                 
                 with col1:
@@ -744,17 +1027,17 @@ def main():
                 for benefit in benefits:
                     st.markdown(f"• {benefit}")
                 
-                # Common ingredients
+                # Enhanced ingredients with protein focus
                 st.markdown("### 🥘 Common Ingredients")
                 ingredients = get_common_ingredients(food_name)
                 for ingredient in ingredients:
                     st.markdown(f"• {ingredient}")
             
             with tab2:
-                # Allergen information
+                # Enhanced allergen information from history
                 allergen_info = get_allergen_info(food_name, allergen_data)
                 
-                # User-specific allergen alerts
+                # User-specific allergen alerts with enhanced styling
                 user_allergens_lower = [allergen.lower() for allergen in st.session_state.user_allergens]
                 common_allergens_lower = [allergen.lower() for allergen in allergen_info.get('common_allergens', [])]
                 may_contain_lower = [allergen.lower() for allergen in allergen_info.get('may_contain', [])]
@@ -769,11 +1052,11 @@ def main():
                     elif user_allergen in may_contain_lower:
                         may_contain_matches.append(user_allergen.title())
                 
-                # Display alerts
+                # Enhanced alert display with animation
                 if allergen_matches:
                     st.markdown(f"""
                     <div class="allergen-alert">
-                        <h3>⚠️ ALLERGEN ALERT</h3>
+                        <h3>🚨 CRITICAL ALLERGEN ALERT</h3>
                         <p>This food contains: <strong>{', '.join(allergen_matches)}</strong></p>
                         <p>You have marked these as allergens to avoid!</p>
                     </div>
@@ -782,7 +1065,7 @@ def main():
                 if may_contain_matches:
                     st.markdown(f"""
                     <div class="allergen-info">
-                        <h3>⚠️ May Contain</h3>
+                        <h3>⚠️ May Contain Alert</h3>
                         <p>This food may contain: <strong>{', '.join(may_contain_matches)}</strong></p>
                         <p>Please check ingredients carefully.</p>
                     </div>
@@ -805,33 +1088,146 @@ def main():
                     for allergen in allergen_info['may_contain']:
                         st.markdown(f"• {allergen}")
                 
-                # Trans fat warning
+                # Enhanced trans fat warning
                 if st.session_state.avoid_trans_fat:
-                    trans_fat_foods = ['french_fries', 'donuts', 'fried_calamari', 'onion_rings']
+                    trans_fat_foods = ['french_fries', 'donuts', 'fried_calamari', 'onion_rings', 'churros', 'chicken_wings', 'fish_and_chips']
                     if food_name in trans_fat_foods:
                         st.markdown("""
                         <div class="allergen-alert">
-                            <h3>⚠️ TRANS FAT WARNING</h3>
-                            <p>This food may contain trans fats from frying oils.</p>
-                            <p>Consider healthier preparation methods!</p>
+                            <h3>🚨 TRANS FAT WARNING</h3>
+                            <p><strong>This food may contain trans fats from frying oils!</strong></p>
+                            <p>⚠️ Trans fats can increase bad cholesterol and heart disease risk</p>
+                            <p>💡 <strong>Healthier alternatives:</strong> Baked, grilled, or air-fried versions</p>
                         </div>
                         """, unsafe_allow_html=True)
+                        
+                        # Add specific recommendations
+                        st.markdown("### 💚 Healthier Preparation Tips")
+                        st.markdown("• **Bake instead of fry** - Use oven at 425°F")
+                        st.markdown("• **Air fry** - Reduces oil by 80%")
+                        st.markdown("• **Use healthy oils** - Olive oil, avocado oil")
+                        st.markdown("• **Grill or steam** - No added fats needed")
+                    else:
+                        st.success("✅ This food is typically low in trans fats!")
+                else:
+                    st.info("💡 Enable trans fat alerts in preferences to get warnings about potentially harmful trans fats.")
             
             with tab3:
-                # Recipe generation
-                st.markdown("### 👨‍🍳 Personalized Recipe")
+                # Professional recipe generation with multiple recipes and limits
+                st.markdown("### 👨‍🍳 Professional Recipes")
+                
+                # Initialize recipe tracking for this food item
+                if 'current_food_recipes' not in st.session_state:
+                    st.session_state.current_food_recipes = {}
+                if 'last_food_analyzed' not in st.session_state:
+                    st.session_state.last_food_analyzed = None
+                
+                # Reset recipe count if analyzing a different food
+                if st.session_state.last_food_analyzed != food_name:
+                    st.session_state.recipe_count = 0
+                    st.session_state.current_food_recipes = {}
+                    st.session_state.last_food_analyzed = food_name
+                
+                # Show current recipe count
+                current_count = st.session_state.get('recipe_count', 0)
+                remaining = 9 - current_count
                 
-                if st.button("🍳 Generate Healthy Recipe", type="primary"):
-                    with st.spinner("👨‍🍳 AI Chef is creating your personalized recipe..."):
-                        recipe = generate_recipe(food_name)
+                if current_count > 0:
+                    st.info(f"📊 **Recipes Generated:** {current_count}/9 | **Remaining:** {remaining}")
+                
+                # Button logic based on recipe count
+                if current_count < 9:
+                    button_text = f"🍳 Generate {min(3, remaining)} More Professional Recipes"
+                    if current_count == 0:
+                        button_text = "🍳 Generate 3 Professional Recipes"
+                    
+                    if st.button(button_text, type="primary", key=f"recipe_btn_{current_count}"):
+                        with st.spinner("👨‍🍳 Professional chef is creating your personalized recipes..."):
+                            # Generate 3 different recipe variations
+                            recipes = generate_multiple_recipes(food_name)
+                            
+                            # Store recipes in session state
+                            if food_name not in st.session_state.current_food_recipes:
+                                st.session_state.current_food_recipes[food_name] = []
+                            st.session_state.current_food_recipes[food_name].extend(recipes)
+                            
+                            st.success(f"✅ {len(recipes)} new recipes generated!")
+                            st.rerun()
+                else:
+                    st.warning("🔒 **Recipe Limit Reached!** You've generated 9 recipes for this food item.")
+                    st.info("💡 **Tip:** Analyze a different food to get more recipe variations!")
+                
+                # Display all generated recipes for this food
+                if food_name in st.session_state.current_food_recipes:
+                    all_recipes = st.session_state.current_food_recipes[food_name]
+                    
+                    for i, recipe_data in enumerate(all_recipes, 1):
+                        st.markdown(f"#### Recipe {i}: {recipe_data['title']}")
                         
-                        st.markdown(f"""
-                        <div class="recipe-section">
-                            {recipe}
-                        </div>
-                        """, unsafe_allow_html=True)
-        
-
+                        # Display food image and recipe
+                        col_img, col_recipe = st.columns([1, 2])
+                        
+                        with col_img:
+                            # Always use styled placeholder - more reliable and professional
+                            # Get recipe style for color
+                            style_colors = {
+                                'healthy': '#28a745',
+                                'quick': '#fd7e14', 
+                                'gourmet': '#6f42c1',
+                                'traditional': '#dc3545',
+                                'fusion': '#e83e8c',
+                                'low-carb': '#20c997',
+                                'protein-rich': '#007bff',
+                                'vegetarian': '#28a745',
+                                'spicy': '#dc3545'
+                            }
+                            
+                            # Get food-specific emoji
+                            food_emojis = {
+                                'caesar_salad': '🥗',
+                                'grilled_salmon': '🐟',
+                                'steak': '🥩',
+                                'pizza': '🍕',
+                                'hamburger': '🍔',
+                                'chicken_curry': '🍛',
+                                'sushi': '🍣',
+                                'tacos': '🌮',
+                                'ice_cream': '🍦',
+                                'chocolate_cake': '🍰'
+                            }
+                            
+                            recipe_style = recipe_data['title'].split()[0].lower()
+                            color = style_colors.get(recipe_style, '#17a2b8')
+                            emoji = food_emojis.get(food_name, '🍽️')
+                            
+                            st.markdown(f"""
+                            <div style="width: 200px; height: 133px; background: linear-gradient(135deg, {color}, #17a2b8); 
+                                       border-radius: 15px; display: flex; align-items: center; justify-content: center; 
+                                       color: white; font-weight: bold; text-align: center; padding: 15px; box-sizing: border-box;
+                                       box-shadow: 0 4px 15px rgba(0,0,0,0.2); margin-bottom: 10px;">
+                                <div>
+                                    <div style="font-size: 3em; margin-bottom: 8px; filter: drop-shadow(2px 2px 4px rgba(0,0,0,0.3));">{emoji}</div>
+                                    <div style="font-size: 0.85em; line-height: 1.2; text-shadow: 1px 1px 2px rgba(0,0,0,0.5);">{recipe_data['title']}</div>
+                                </div>
+                            </div>
+                            """, unsafe_allow_html=True)
+                        
+                        with col_recipe:
+                            st.markdown(f"""
+                            <div class="recipe-section">
+                                {recipe_data['recipe']}
+                            </div>
+                            """, unsafe_allow_html=True)
+                        
+                        st.markdown("---")
+                
+                # Reset button for new food analysis
+                if current_count > 0:
+                    if st.button("🔄 Clear All Recipes (Start Fresh)", type="secondary"):
+                        st.session_state.recipe_count = 0
+                        st.session_state.current_food_recipes = {}
+                        st.success("✅ All recipes cleared! You can now generate new ones.")
+                        st.rerun()
 
 if __name__ == "__main__":
     main() 

health_info.json

@@ -0,0 +1,157 @@
+{
+  "grilled_salmon": {
+    "calories": "231",
+    "protein": "25.4g",
+    "carbs": "0g",
+    "fat": "13.4g",
+    "fiber": "0g",
+    "health_score": "Excellent",
+    "benefits": [
+      "Rich in high-quality protein for muscle building",
+      "Excellent source of omega-3 fatty acids for heart health",
+      "Contains vitamin D for bone health",
+      "High in B vitamins for energy metabolism",
+      "Anti-inflammatory properties"
+    ]
+  },
+  "pizza": {
+    "calories": "285",
+    "protein": "12.2g",
+    "carbs": "35.6g",
+    "fat": "10.4g",
+    "fiber": "2.5g",
+    "health_score": "Good",
+    "benefits": [
+      "Provides carbohydrates for energy",
+      "Contains protein from cheese",
+      "Tomato sauce provides lycopene antioxidants",
+      "Can be made healthier with vegetable toppings"
+    ]
+  },
+  "chicken_curry": {
+    "calories": "217",
+    "protein": "19.8g",
+    "carbs": "9.2g",
+    "fat": "11.5g",
+    "fiber": "2.1g",
+    "health_score": "Good",
+    "benefits": [
+      "High-quality lean protein source",
+      "Spices provide anti-inflammatory compounds",
+      "Contains turmeric with curcumin benefits",
+      "Good source of essential amino acids"
+    ]
+  },
+  "caesar_salad": {
+    "calories": "158",
+    "protein": "7.3g",
+    "carbs": "8.9g",
+    "fat": "11.2g",
+    "fiber": "3.2g",
+    "health_score": "Good",
+    "benefits": [
+      "Rich in vitamins A and K from romaine lettuce",
+      "Contains calcium from parmesan cheese",
+      "Good source of folate",
+      "Provides dietary fiber for digestion"
+    ]
+  },
+  "hamburger": {
+    "calories": "540",
+    "protein": "25.8g",
+    "carbs": "40.3g",
+    "fat": "31.0g",
+    "fiber": "2.2g",
+    "health_score": "Poor",
+    "benefits": [
+      "High protein content for muscle maintenance",
+      "Provides iron from beef",
+      "Contains B vitamins",
+      "Can be made healthier with lean meat and whole grain bun"
+    ]
+  },
+  "sushi": {
+    "calories": "200",
+    "protein": "8.8g",
+    "carbs": "43.8g",
+    "fat": "0.6g",
+    "fiber": "0.3g",
+    "health_score": "Good",
+    "benefits": [
+      "Low in calories and fat",
+      "High-quality protein from fish",
+      "Contains omega-3 fatty acids",
+      "Seaweed provides iodine and minerals"
+    ]
+  },
+  "chocolate_cake": {
+    "calories": "352",
+    "protein": "5.0g",
+    "carbs": "50.7g",
+    "fat": "16.4g",
+    "fiber": "2.0g",
+    "health_score": "Poor",
+    "benefits": [
+      "Provides quick energy from carbohydrates",
+      "Dark chocolate contains antioxidants",
+      "Can boost mood temporarily",
+      "Best enjoyed in moderation"
+    ]
+  },
+  "french_fries": {
+    "calories": "365",
+    "protein": "4.0g",
+    "carbs": "63.2g",
+    "fat": "17.0g",
+    "fiber": "5.7g",
+    "health_score": "Poor",
+    "benefits": [
+      "Provides potassium from potatoes",
+      "Contains some vitamin C",
+      "Source of carbohydrates for energy",
+      "Better when baked instead of fried"
+    ]
+  },
+  "ice_cream": {
+    "calories": "207",
+    "protein": "3.5g",
+    "carbs": "23.6g",
+    "fat": "11.0g",
+    "fiber": "0.7g",
+    "health_score": "Poor",
+    "benefits": [
+      "Contains calcium from dairy",
+      "Provides some protein",
+      "Can be part of balanced diet in moderation",
+      "Frozen yogurt alternatives are healthier"
+    ]
+  },
+  "tacos": {
+    "calories": "226",
+    "protein": "9.4g",
+    "carbs": "18.0g",
+    "fat": "13.8g",
+    "fiber": "3.2g",
+    "health_score": "Good",
+    "benefits": [
+      "Balanced macronutrients",
+      "Contains protein from meat or beans",
+      "Vegetables provide vitamins and minerals",
+      "Can be made very healthy with fresh ingredients"
+    ]
+  },
+  "steak": {
+    "calories": "271",
+    "protein": "26.1g",
+    "carbs": "0g",
+    "fat": "17.4g",
+    "fiber": "0g",
+    "health_score": "Good",
+    "benefits": [
+      "Excellent source of high-quality protein",
+      "Rich in iron and zinc",
+      "Contains vitamin B12",
+      "Provides essential amino acids"
+    ]
+  }
+}