Update app.py

app.py

@@ -1,14 +1,17 @@
 import streamlit as st
 import json
 import os
+import uuid
+from datetime import datetime
+from io import BytesIO
+from decimal import Decimal  # Add this import for DynamoDB float handling
+
+# Third-party library imports
 import boto3
 from PIL import Image
 import firebase_admin
 from firebase_admin import credentials, auth
 import pandas as pd
-import uuid
-from datetime import datetime
-from io import BytesIO
 import streamlit_tags as st_tags
 from dotenv import load_dotenv
 
@@ -164,13 +167,17 @@ def save_metadata(user_id, s3_path, food_name, portion_size, portion_unit, cooki
         image_id = str(uuid.uuid4())
         timestamp = datetime.now().isoformat()
         
+        # Ensure portion_size is a Decimal (DynamoDB doesn't support float)
+        if not isinstance(portion_size, Decimal):
+            portion_size = Decimal(str(portion_size))
+        
         # Create item for DynamoDB
         item = {
             'image_id': image_id,
             'user_id': user_id,
             'upload_timestamp': timestamp,
             'food_name': food_name,
-            'portion_size': portion_size,
+            'portion_size': portion_size,  # Decimal type
             'portion_unit': portion_unit,
             'cooking_method': cooking_method,
             'ingredients': ingredients,
@@ -207,6 +214,10 @@ if "tokens" not in st.session_state:
 if "uploads_count" not in st.session_state:
     st.session_state["uploads_count"] = 0
 
+# Initialize food items list for storing multiple annotations
+if "food_items" not in st.session_state:
+    st.session_state["food_items"] = []
+
 # Streamlit Layout - Authentication Section
 st.sidebar.title("🔑 User Authentication")
 auth_option = st.sidebar.radio("Select an option", ["Login", "Sign Up", "Logout"])
@@ -252,22 +263,31 @@ if "user_id" not in st.session_state and not st.session_state.get("demo_mode", F
     # Add links to guidelines and terms
     st.markdown("### 📚 While You're Here")
     st.markdown("Take a moment to read our guidelines and token system:")
-    col1, col2, col3 = st.columns(3)
-    with col1:
-        if st.button("Participation Guidelines"):
+    
+    # Use expanders instead of columns for better document display
+    with st.expander("📋 Participation Guidelines"):
+        try:
             with open("PARTICIPATION_GUIDELINES.md", "r") as f:
                 guidelines = f.read()
-            st.markdown(guidelines)
-    with col2:
-        if st.button("Token Rewards"):
+            st.markdown(guidelines, unsafe_allow_html=True)
+        except Exception as e:
+            st.error(f"Could not load guidelines: {e}")
+    
+    with st.expander("🪙 Token Rewards System"):
+        try:
             with open("TOKEN_REWARDS.md", "r") as f:
                 rewards = f.read()
-            st.markdown(rewards)
-    with col3:
-        if st.button("Terms of Service"):
+            st.markdown(rewards, unsafe_allow_html=True)
+        except Exception as e:
+            st.error(f"Could not load rewards information: {e}")
+    
+    with st.expander("📜 Terms of Service"):
+        try:
             with open("TERMS_OF_SERVICE.md", "r") as f:
                 terms = f.read()
-            st.markdown(terms)
+            st.markdown(terms, unsafe_allow_html=True)
+        except Exception as e:
+            st.error(f"Could not load terms: {e}")
     
     st.stop()
 
@@ -296,7 +316,7 @@ if uploaded_file:
 if "original_image" in st.session_state:
     original_img = st.session_state["original_image"]
     
-    # Process the image - resize and compress
+    # Process the image - resize and compress with more visible difference
     processed_img = resize_image(original_img, max_size=512, quality=85)
     st.session_state["processed_image"] = processed_img
     
@@ -305,21 +325,36 @@ if "original_image" in st.session_state:
     processed_size = get_image_size_kb(processed_img)
     size_reduction = ((original_size - processed_size) / original_size) * 100 if original_size > 0 else 0
 
-    # Display images side by side
+    # Display images side by side with border to highlight differences
     col1, col2 = st.columns(2)
     with col1:
         st.subheader("📷 Original Image")
+        st.markdown(f"<div style='border:2px solid red;padding:5px;'>", unsafe_allow_html=True)
         st.image(original_img, caption=f"Original ({original_img.width}x{original_img.height} px, {original_size:.1f} KB)", use_container_width=True)
+        st.markdown("</div>", unsafe_allow_html=True)
     with col2:
         st.subheader("🖼️ Processed Image")
+        st.markdown(f"<div style='border:2px solid green;padding:5px;'>", unsafe_allow_html=True)
         st.image(processed_img, caption=f"Processed ({processed_img.width}x{processed_img.height} px, {processed_size:.1f} KB)", use_container_width=True)
+        st.markdown("</div>", unsafe_allow_html=True)
     
     # Show size reduction
     if size_reduction > 5:  # Only show if there's a meaningful reduction
         st.success(f"✅ Image size reduced by {size_reduction:.1f}% for faster uploads and processing")
 
+    # Display existing food annotations if any
+    if st.session_state["food_items"]:
+        st.subheader("📋 Added Food Items")
+        for i, item in enumerate(st.session_state["food_items"]):
+            with st.expander(f"🍽️ {item['food_name']} ({item['portion_size']} {item['portion_unit']})"):
+                st.write(f"**Cooking Method:** {item['cooking_method']}")
+                st.write(f"**Ingredients:** {', '.join(item['ingredients'])}")
+                if st.button(f"Remove Item #{i+1}", key=f"remove_{i}"):
+                    st.session_state["food_items"].pop(i)
+                    st.experimental_rerun()
+
     # Food metadata form
-    st.subheader("🍲 Food Details")
+    st.subheader("🍲 Add Food Details")
     
     food_name = st.selectbox("Food Name", options=[""] + FOOD_SUGGESTIONS, index=0)
     if food_name == "":
@@ -327,7 +362,7 @@ if "original_image" in st.session_state:
     
     col1, col2 = st.columns(2)
     with col1:
-        portion_size = st.number_input("Portion Size", min_value=0.1, step=0.1)
+        portion_size = st.number_input("Portion Size", min_value=0.1, step=0.1, format="%.2f")
     with col2:
         portion_unit = st.selectbox("Unit", options=UNIT_OPTIONS)
     
@@ -341,50 +376,87 @@ if "original_image" in st.session_state:
         maxtags=5
     )
     
-    # Submit button
-    if st.button("📤 Submit Food Image"):
-        with st.spinner("Processing your submission..."):
-            # Determine image quality (simplified version)
-            image_quality = "high" if original_img.width >= 1000 and original_img.height >= 1000 else "standard"
-            
-            # Check if metadata is complete
-            has_metadata = bool(food_name and portion_size and portion_unit and cooking_method)
-            
-            # Check if the food is in a unique category (simplified)
-            is_unique_category = food_name not in ["Pizza", "Burger", "Pasta", "Salad"]
-            
-            # Calculate tokens
-            tokens_awarded = calculate_tokens(image_quality, has_metadata, is_unique_category)
-            
-            # Upload image to S3
-            s3_path = upload_to_s3(processed_img, st.session_state["user_id"])
-            
-            if s3_path:
-                # Save metadata to DynamoDB
-                success = save_metadata(
-                    st.session_state["user_id"],
-                    s3_path,
-                    food_name,
-                    float(portion_size),
-                    portion_unit,
-                    cooking_method,
-                    ingredients,
-                    tokens_awarded
-                )
-                
-                if success:
-                    st.session_state["tokens"] += tokens_awarded
-                    st.session_state["uploads_count"] += 1
-                    st.success(f"✅ Food image uploaded successfully! You earned {tokens_awarded} tokens.")
-                    
-                    # Clear the form and image for a new submission
-                    st.session_state.pop("original_image", None)
-                    st.session_state.pop("processed_image", None)
-                    st.experimental_rerun()
-                else:
-                    st.error("Failed to save metadata. Please try again.")
+    # Add this food to the list
+    col1, col2 = st.columns([1, 1])
+    
+    with col1:
+        if st.button("➕ Add This Food Item"):
+            if food_name and portion_size and portion_unit and cooking_method:
+                # Add the food item to the session state
+                st.session_state["food_items"].append({
+                    "food_name": food_name,
+                    "portion_size": portion_size,
+                    "portion_unit": portion_unit,
+                    "cooking_method": cooking_method,
+                    "ingredients": ingredients
+                })
+                st.success(f"✅ Added {food_name} to your submission")
+                st.experimental_rerun()
+            else:
+                st.error("❌ Please fill in all required fields")
+    
+    # Submit all foods button
+    with col2:
+        if st.button("📤 Submit All Food Items"):
+            if not st.session_state["food_items"]:
+                st.error("❌ Please add at least one food item before submitting")
             else:
-                st.error("Failed to upload image. Please try again.")
+                with st.spinner("Processing your submission..."):
+                    all_saved = True
+                    total_tokens = 0
+                    
+                    # Determine image quality (simplified version)
+                    image_quality = "high" if original_img.width >= 1000 and original_img.height >= 1000 else "standard"
+                    
+                    # Upload image to S3 once
+                    s3_path = upload_to_s3(processed_img, st.session_state["user_id"])
+                    
+                    if s3_path:
+                        # Save each food item with the same image
+                        for food_item in st.session_state["food_items"]:
+                            # Check if metadata is complete
+                            has_metadata = True  # Already validated
+                            
+                            # Check if the food is in a unique category (simplified)
+                            is_unique_category = food_item["food_name"] not in ["Pizza", "Burger", "Pasta", "Salad"]
+                            
+                            # Calculate tokens for this item
+                            tokens_awarded = calculate_tokens(image_quality, has_metadata, is_unique_category)
+                            total_tokens += tokens_awarded
+                            
+                            # Convert float to Decimal for DynamoDB
+                            portion_size_decimal = Decimal(str(food_item["portion_size"]))
+                            
+                            # Save metadata to DynamoDB
+                            success = save_metadata(
+                                st.session_state["user_id"],
+                                s3_path,
+                                food_item["food_name"],
+                                portion_size_decimal,  # Use Decimal type
+                                food_item["portion_unit"],
+                                food_item["cooking_method"],
+                                food_item["ingredients"],
+                                tokens_awarded
+                            )
+                            
+                            if not success:
+                                all_saved = False
+                                break
+                        
+                        if all_saved:
+                            st.session_state["tokens"] += total_tokens
+                            st.session_state["uploads_count"] += 1
+                            st.success(f"✅ All food items uploaded successfully! You earned {total_tokens} tokens.")
+                            
+                            # Clear the form and image for a new submission
+                            st.session_state.pop("original_image", None)
+                            st.session_state.pop("processed_image", None)
+                            st.session_state["food_items"] = []
+                            st.experimental_rerun()
+                        else:
+                            st.error("Failed to save some items. Please try again.")
+                    else:
+                        st.error("Failed to upload image. Please try again.")
 
 # Display earned tokens
 st.sidebar.markdown("---")
@@ -408,4 +480,4 @@ if st.sidebar.button("Token Rewards System"):
 if st.sidebar.button("Terms of Service"):
     with open("TERMS_OF_SERVICE.md", "r") as f:
         terms = f.read()
-    st.sidebar.markdown(terms)
+    st.sidebar.markdown(terms)