Update app.py

app.py

@@ -22,7 +22,7 @@ def configure_gemini(api_key):
     return genai.GenerativeModel('gemini-2.0-flash-thinking-exp')
 
 model = configure_gemini(os.environ['GOOGLE_API_KEY'])
-            
+
 # Initialize Gemini models
 llm_flash_exp = ChatGoogleGenerativeAI(
     model="gemini-2.0-flash-exp",
@@ -92,7 +92,6 @@ class SmartShoppingAssistant:
             except Exception:
                 quantity = 1
 
-            # Avoid duplicates by checking the cleaned product name
             if clean_name in matched_products:
                 continue
 
@@ -110,15 +109,11 @@ class SmartShoppingAssistant:
         
     def setup_agent(self):
         """Set up the LangChain agent with necessary tools (if needed)"""
-        # In this revised version we will directly call our fuzzy search function,
-        # so the tool is not used to convert to a string.
         def search_products(query):
             try:
-                # Split into individual product entries
                 product_entries = [entry.strip() for entry in query.split('or')]
                 results = self.search_products_fuzzy(product_entries)
                 if not results.empty:
-                    # Create a formatted string with each product’s quantity and price
                     formatted_results = results.apply(
                         lambda x: f"{x['ProductName']} (Quantity: {x['Quantity']}) - Price: ${x['RetailPrice']:.2f}",
                         axis=1
@@ -153,7 +148,6 @@ class SmartShoppingAssistant:
               can be displayed and the total computed.
         """
         try:
-            # Step 1: Extract items and quantities from the query.
             extraction_prompt = f"""
             Extract the products and their quantities from this shopping request.
             If a quantity is not specified, assume 1.
@@ -165,11 +159,8 @@ class SmartShoppingAssistant:
             """
             
             extracted_items = llm_flash_exp.predict(extraction_prompt)
-            # Step 2: Match the extracted items with your catalogue.
             matched_products_str = self.match_products_with_catalogue(extracted_items)
-            # Parse the matched products string into a list of entries.
             product_entries = [line.strip() for line in matched_products_str.splitlines() if line.strip()]
-            # Step 3: Do a fuzzy search and get the DataFrame result.
             results_df = self.search_products_fuzzy(product_entries)
             return results_df
         except Exception as e:
@@ -205,7 +196,7 @@ class SmartShoppingAssistant:
 def add_to_cart(product):
     if 'cart' not in st.session_state:
         st.session_state.cart = []
-    # Check if product exists in the cart
+    # Check if product exists in the cart and update quantity if so.
     existing = next((item for item in st.session_state.cart if item['ProductName'] == product['ProductName']), None)
     if existing:
         existing['Quantity'] += product['Quantity']
@@ -242,13 +233,22 @@ def main():
     st.set_page_config(page_title="Smart Shopping Assistant", layout="wide")
     st.title("🛒 Smart Shopping Assistant")
     
+    # Load product data only once.
     @st.cache_data
     def load_product_data():
-        return pd.read_csv('supermarket4i.csv')  # Adjust filename/path as needed
+        return pd.read_csv('supermarket4i.csv')
     
     df = load_product_data()
     assistant = SmartShoppingAssistant(df)
     
+    # Initialize session state variables if not present.
+    if 'query' not in st.session_state:
+        st.session_state.query = ""
+    if 'last_results' not in st.session_state:
+        st.session_state.last_results = None
+    if 'cart' not in st.session_state:
+        st.session_state.cart = []
+    
     with st.sidebar:
         st.header("Upload Shopping List")
         uploaded_file = st.file_uploader(
@@ -269,45 +269,50 @@ def main():
                         st.session_state.query = extracted_text
             except Exception as e:
                 st.error(f"Error processing file: {str(e)}")
-
+    
     col1, col2 = st.columns([2, 1])
     
     with col1:
         st.header("Search Products")
+        # Use session_state query so that we can clear it after search if desired.
         query = st.text_area(
             "Describe what you're looking for (include quantities if needed):",
             height=100,
-            value=st.session_state.get('query', '')
+            value=st.session_state.query
         )
         
-        if st.button("Search"):
+        if st.button("Search", key="search_button"):
             if query:
                 with st.spinner("Searching..."):
                     results = assistant.process_natural_language_query(query)
                     st.session_state.last_results = results
-                    
-                # If results is a string (an error message), show it.
-                if isinstance(results, str):
-                    st.write(results)
-                else:
-                    st.subheader("Results")
-                    # Display each product with its quantity, price and an Add to Cart button.
-                    for index, row in results.iterrows():
-                        cola, colb = st.columns([3, 1])
-                        with cola:
+                    # Optionally clear the query after search:
+                    st.session_state.query = ""
+        
+        # Display search results if available.
+        if st.session_state.last_results is not None:
+            if isinstance(st.session_state.last_results, str):
+                st.write(st.session_state.last_results)
+            else:
+                st.subheader("Results")
+                for index, row in st.session_state.last_results.iterrows():
+                    with st.container():
+                        cols = st.columns([3, 1])
+                        with cols[0]:
                             st.write(f"**{row['ProductName']}**")
                             st.write(f"Price: ${row['RetailPrice']:.2f} | Qty: {row['Quantity']}")
-                        with colb:
+                        with cols[1]:
+                            # When a product is added, update the cart state without forcing a full rerun.
                             if st.button("Add", key=f"add_{index}"):
                                 add_to_cart(row.to_dict())
-                    
-                    # Show the total cost for the search results
-                    total_search = (results['RetailPrice'] * results['Quantity']).sum()
-                    st.markdown(f"**Total for these items: ${total_search:.2f}**")
+                                st.success(f"Added {row['ProductName']} to cart")
+    
+                total_search = (st.session_state.last_results['RetailPrice'] * st.session_state.last_results['Quantity']).sum()
+                st.markdown(f"**Total for these items: ${total_search:.2f}**")
     
     with col2:
         st.header("Shopping Cart")
-        if 'cart' in st.session_state and st.session_state.cart:
+        if st.session_state.cart:
             total_cart = 0
             for item in st.session_state.cart:
                 cols = st.columns([3, 1, 1])
@@ -319,6 +324,7 @@ def main():
                 with cols[2]:
                     if st.button("❌", key=f"del_{item['ProductName']}"):
                         remove_from_cart(item['ProductName'])
+                        # We use experimental_rerun here so that the cart updates immediately.
                         st.experimental_rerun()
                 total_cart += item['RetailPrice'] * item['Quantity']
             st.divider()