Update app.py

app.py

@@ -32,14 +32,18 @@ llm_flash_exp = ChatGoogleGenerativeAI(
 class SmartShoppingAssistant:
     def __init__(self, products_df):
         self.df = products_df
+        # Preprocess product names for faster matching
+        self.df['CleanName'] = self.df['ProductName'].str.upper().str.strip().str.replace(r'\s+', ' ', regex=True)
+        self.product_names = self.df['CleanName'].tolist()
         self.memory = ConversationBufferMemory(memory_key="chat_history", return_messages=True)
         self.setup_agent()
-    
-    def find_closest_product(self, product_name, threshold=0.6):
+
+    def find_closest_product(self, product_name, threshold=0.7):  # Increased threshold
+        product_name = product_name.upper().strip()
         matches = get_close_matches(
-            product_name.upper(),
-            self.df['ProductName'].str.upper().tolist(),
-            n=3,  # Increased to get more potential matches
+            product_name,
+            self.product_names,
+            n=3,
             cutoff=threshold
         )
         return matches if matches else []
@@ -75,26 +79,29 @@ class SmartShoppingAssistant:
             return f"Error matching products: {str(e)}"
     
     def search_products_fuzzy(self, product_names_with_quantities):
-        """Search for products using fuzzy matching with quantity information"""
+        """Improved fuzzy search with batch processing"""
         results = pd.DataFrame()
+        matched_products = set()
+        
         for item in product_names_with_quantities:
             product_info = item.split('quantity:')
-            product_name = product_info[0].strip()
+            clean_name = product_info[0].strip().upper().replace('PRODUCTNAME ==', '').strip(' "\'')
             quantity = int(product_info[1].strip()) if len(product_info) > 1 else 1
-            
-            # Clean up product name
-            if 'ProductName ==' in product_name:
-                product_name = product_name.split('==')[1].strip(' "\'')
-            
-            closest_matches = self.find_closest_product(product_name)
+
+            if clean_name in matched_products:
+                continue  # Skip already matched products
+
+            closest_matches = self.find_closest_product(clean_name)
             for match in closest_matches:
-                matched_products = self.df[self.df['ProductName'].str.upper() == match.upper()]
-                if not matched_products.empty:
-                    matched_products['Quantity'] = quantity
-                    results = pd.concat([results, matched_products])
-                    break
+                matched = self.df[self.df['CleanName'] == match]
+                if not matched.empty:
+                    matched = matched.copy()
+                    matched['Quantity'] = quantity
+                    results = pd.concat([results, matched])
+                    matched_products.add(clean_name)
+                    break  # Take first good match
         
-        return results
+        return results.drop_duplicates(subset=['CleanName'])
         
     def setup_agent(self):
         """Set up the LangChain agent with necessary tools"""
@@ -180,14 +187,50 @@ class SmartShoppingAssistant:
         except Exception as e:
             return f"Error processing PDF: {str(e)}"
 
-# Main function remains the same
+
+# Add cart management functions
+def add_to_cart(product):
+    if 'cart' not in st.session_state:
+        st.session_state.cart = []
+        
+    # Check if product exists in cart
+    existing = next((item for item in st.session_state.cart if item['ProductName'] == product['ProductName']), None)
+    if existing:
+        existing['Quantity'] += product['Quantity']
+    else:
+        st.session_state.cart.append(product)
+
+def remove_from_cart(product_name):
+    st.session_state.cart = [item for item in st.session_state.cart if item['ProductName'] != product_name]
+
+def generate_receipt():
+    from fpdf import FPDF
+    pdf = FPDF()
+    pdf.add_page()
+    pdf.set_font("Arial", size=12)
+    
+    pdf.cell(200, 10, txt="Bon Marche Receipt", ln=1, align='C')
+    pdf.cell(200, 10, txt=f"Date: {pd.Timestamp.now().strftime('%Y-%m-%d %H:%M')}", ln=1)
+    
+    total = 0
+    for item in st.session_state.cart:
+        price = item['RetailPrice'] * item['Quantity']
+        pdf.cell(200, 10, 
+                 txt=f"{item['ProductName']} x{item['Quantity']} - ${price:.2f}",
+                 ln=1)
+        total += price
+    
+    pdf.cell(200, 10, txt=f"Total: ${total:.2f}", ln=1)
+    return pdf.output(dest='S').encode('latin1')
+
+# Update main function
 def main():
     st.set_page_config(page_title="Smart Shopping Assistant", layout="wide")
     st.title("🛒 Smart Shopping Assistant")
     
     @st.cache_data
     def load_product_data():
-        return pd.read_csv('supermarket4.csv')
+        return pd.read_csv('supermarket4i.csv')  # Ensure correct filename
     
     df = load_product_data()
     assistant = SmartShoppingAssistant(df)
@@ -220,24 +263,56 @@ def main():
         query = st.text_area(
             "Describe what you're looking for (include quantities if needed):",
             height=100,
-            placeholder="Example: 2 boxes of healthy breakfast cereals under $5, 1 gallon of milk",
             value=st.session_state.get('query', '')
         )
         
         if st.button("Search"):
             if query:
-                with st.spinner("Searching for products..."):
+                with st.spinner("Searching..."):
                     results = assistant.process_natural_language_query(query)
-                    st.write("### Results")
-                    st.write(results)
-            else:
-                st.warning("Please enter a search query or upload a shopping list.")
+                    st.session_state.last_results = results
+                    
+                    # Display results with add to cart buttons
+                    if isinstance(results, str):
+                        st.write(results)
+                    else:
+                        for _, row in results.iterrows():
+                            cola, colb = st.columns([3,1])
+                            with cola:
+                                st.write(f"**{row['ProductName']}**")
+                                st.write(f"Price: ${row['RetailPrice']} | Qty: {row['Quantity']}")
+                            with colb:
+                                if st.button("Add", key=row['ProductName']):
+                                    add_to_cart(row.to_dict())
     
     with col2:
         st.header("Shopping Cart")
-        if 'cart' not in st.session_state:
-            st.session_state.cart = []
-        st.write("Your cart is empty" if not st.session_state.cart else "Cart items here")
+        if 'cart' in st.session_state and st.session_state.cart:
+            total = 0
+            for item in st.session_state.cart:
+                cols = st.columns([3,1,1])
+                with cols[0]:
+                    st.write(f"{item['ProductName']} x{item['Quantity']}")
+                with cols[1]:
+                    st.write(f"${item['RetailPrice'] * item['Quantity']:.2f}")
+                with cols[2]:
+                    if st.button("❌", key=f"del_{item['ProductName']}"):
+                        remove_from_cart(item['ProductName'])
+                        st.rerun()
+                total += item['RetailPrice'] * item['Quantity']
+            st.divider()
+            st.write(f"**Total: ${total:.2f}**")
+            
+            if st.button("Checkout"):
+                receipt = generate_receipt()
+                st.download_button(
+                    label="Download Receipt",
+                    data=receipt,
+                    file_name="bon_marche_receipt.pdf",
+                    mime="application/pdf"
+                )
+        else:
+            st.write("Your cart is empty")
 
 if __name__ == "__main__":
     main()