Update app.py

app.py

@@ -83,7 +83,7 @@ def score(main_product, main_url, search, logger, log_area):
 
     cosine_sim_scores = []
 
-    logger.write("\n\nCreating Similar product Embeddings ------\n")
+    logger.write("\n\nCreating Similar product Embeddings ---------->\n")
     log_area.text(logger.getvalue())
 
     for product in data:
@@ -107,23 +107,23 @@ st.title("Product Infringement Checker")
 # Inputs
 main_product = st.text_input('Enter Main Product Name', 'Philips led 7w bulb')
 main_url = st.text_input('Enter Main Product Manual URL', 'https://www.assets.signify.com/is/content/PhilipsConsumer/PDFDownloads/Colombia/technical-sheets/ODLI20180227_001-UPD-es_CO-Ficha_Tecnica_LED_MR16_Master_7W_Dim_12V_CRI90.pdf')
-search = st.selectbox('Choose Search Engine', ['duckduckgo', 'google', 'archive', 'github', 'wikipedia', 'all'])
+search_method = st.selectbox('Choose Search Engine', ['duckduckgo', 'google', 'archive', 'github', 'wikipedia', 'all'])
 
 if st.button('Check for Infringement'):
     log_output = st.empty()  # Placeholder for log output
 
     with st.spinner('Processing...'):
         with StreamCapture() as logger:
-            score(main_product, main_url, search, logger, log_output)
+            cosine_sim_scores, main_result = score(main_product, main_url, search_method, logger, log_output)
 
     st.success('Processing complete!')
 
     st.subheader("Cosine Similarity Scores")
 
-    cosine_sim_scores, main_result = score(main_product, main_url, search, logger, log_output)
+    #  = score(main_product, main_url, search, logger, log_output)
     tags = ['Introduction', 'Specifications', 'Product Overview', 'Safety Information', 'Installation Instructions', 'Setup and Configuration', 'Operation Instructions', 'Maintenance and Care', 'Troubleshooting', 'Warranty Information', 'Legal Information']
 
     for product, link, index, value in cosine_sim_scores:
         if not index:
             st.write(f"Product: {product}, Link: {link}")
-        st.write(f"{tags[index]:<20} Cosine Similarity Score: {value:.2f}")
+        st.write(f"{tags[index]:<20} Cosine Similarity Score: {value:.2f}")