Update app.py

app.py

@@ -1,86 +1,3 @@
-# import streamlit as st
-# import pickle
-
-# # Function to load pickle files
-# def read_pickle_files(pickle_file):
-#     with open(pickle_file, 'rb') as f:
-#         return pickle.load(f)
-
-# # Load the necessary pickle files
-# cross_sell_data = read_pickle_files("fynd.cross_sell_recommendations-000000000000000000000001s.pkl")
-# upsell_data = read_pickle_files("fynd.up_sell_recommendations_000000000000000000000002s.pkl")
-# uid_name_pairs = read_pickle_files("uid_name_pairs.pkl")
-# uid_image_html_pairs = read_pickle_files("uid_image_html_pairs.pkl")
-
-# # Create a mapping from product_id to product name for dropdown
-# product_name_to_id = {name: uid for name, uid in uid_name_pairs.items()}
-
-# # Create a reverse mapping from product_id to product_name for display purposes
-# product_id_to_name = {uid: name for name, uid in uid_name_pairs.items()}
-
-# # Function to extract product list from recommendation data
-# def extract_product_list(recommendation_data):
-#     product_ids = [entry['product_id'] for entry in recommendation_data]
-#     # Map the product IDs to names for the dropdown
-#     return [product_id_to_name[product_id] for product_id in product_ids if product_id in product_id_to_name]
-
-# # Extract recommendations for a specific product_id
-# def get_recommendations(product_id, recommendation_data):
-#     for product in recommendation_data:
-#         if product['product_id'] == product_id:
-#             return product['recommendations']
-#     return []
-
-# # Streamlit App Layout
-# st.title("Cross-Sell & Up-Sell Recommendations")
-
-# # Dropdown for selecting recommendation type
-# recommendation_type = st.selectbox("Select recommendation type:", ["Cross-sell", "Up-sell"])
-
-# # Choose the appropriate data based on recommendation type
-# if recommendation_type == "Cross-sell":
-#     recommendations_data = cross_sell_data
-# elif recommendation_type == "Up-sell":
-#     recommendations_data = upsell_data
-
-# # Get the list of product names for the dropdown
-# product_list = extract_product_list(recommendations_data)
-
-# # Dropdown for selecting a product by name
-# selected_product_name = st.selectbox("Select a product:", product_list)
-
-# # Get the selected product's ID using the name
-# selected_product_id = product_name_to_id.get(selected_product_name)
-
-# # Display the image of the selected product using the image URL
-# if selected_product_id:
-#     #st.subheader(f"Selected Product: {selected_product_name}")
-    
-#     # Check if the product's ID has an associated image HTML and use the image URL
-#     if selected_product_id in uid_image_html_pairs:
-#         image_url = uid_image_html_pairs[selected_product_id]
-#         st.image(image_url, use_column_width=False, width=200)  # Set width to make image smaller
-
-# # Display recommendations for the selected product
-# if selected_product_id:
-#     recommendations = get_recommendations(selected_product_id, recommendations_data)
-    
-#     if recommendations:
-#         #st.subheader(f"Recommendations:")
-#         for recommendation in recommendations:
-#             product_name = recommendation.get('product_name')
-#             recommended_product_id = recommendation.get('product_id')
-
-#             # Display the image of each recommended product using the image URL
-#             if recommended_product_id in uid_image_html_pairs:
-#                 recommended_image_url = uid_image_html_pairs[recommended_product_id]
-#                 st.image(recommended_image_url, caption=product_name, use_column_width=False, width=150)  # Set width to make images smaller
-            
-#             # Display the product name
-#             st.write(f"Product Name: {product_name}")
-#     else:
-#         st.write("No recommendations found for this product.")
-
 import streamlit as st
 import pickle
 from html_information2 import html2