Update app.py

app.py

@@ -26,20 +26,20 @@ data = load_json_from_url(json_url)
 # Extract unique brands
 brands = sorted(list(set([item["brand"] for item in data])))
 
-# Web Scraping function to get product description from Ethos website
+# Function to scrape Ethos product description using the specified selector
 def scrape_ethos_description(product_link):
     try:
         response = requests.get(product_link)
         soup = BeautifulSoup(response.text, 'html.parser')
 
-        # Assuming product description is within a specific class or ID, find it
-        description = soup.find('div', class_='product-description')  # Example class, adjust based on actual site structure
+        # Target the specific selector to extract the description
+        description = soup.select_one('#brand_collection > div > div.lHeight_100.spec_editorNotes > div > p:nth-child(5)')
         if description:
             return description.get_text(strip=True)
         else:
-            return "No detailed description available on Ethos site."
+            return "No detailed description available from Ethos."
     except Exception as e:
-        return f"Error fetching details from Ethos site: {str(e)}"
+        return f"Error fetching details from Ethos: {str(e)}"
 
 # Streamlit UI
 st.title("Watch Description Generator")
@@ -67,19 +67,19 @@ if selected_brand != "Select":
         if image_url:
             st.image(image_url, caption=f"{watch_data['name']} Image")
 
-        # Get the Ethos product link for web scraping (assuming 'url' key exists in your JSON)
+        # Get the Ethos product link for web scraping
         product_link = watch_data.get("url", None)
         if product_link:
             st.write(f"Fetching details from: [Product Page]({product_link})")
 
-            # Scrape Ethos product page for more description
+            # Scrape Ethos product page for description
             ethos_description = scrape_ethos_description(product_link)
-            st.write("### Ethos Product Description")
+            st.write("### Ethos Product Description (Extracted)")
             st.write(ethos_description)
         else:
             st.warning("No Ethos link available for this SKU.")
 
-        # Generate watch description based on attributes and scraped content
+        # Generate a watch description based on attributes and scraped content
         attributes = {
             "brand": watch_data["brand"],
             "name": watch_data.get("name", "Unknown Watch"),
@@ -94,7 +94,7 @@ if selected_brand != "Select":
             "strap_material": watch_data.get("strap_material", "Unknown Strap Material")
         }
 
-        # Create a detailed description prompt combining scraped content and attributes
+        # Combine Ethos description and attributes into a prompt
         input_text = f"""Generate a detailed 100-word description for the following watch:
 Brand: {attributes['brand']}
 Name: {attributes['name']}
@@ -111,39 +111,39 @@ Strap Material: {attributes['strap_material']}
 Additional details from Ethos:
 {ethos_description}
 
-Description: Provide a luxurious, detailed description focusing on the craftsmanship, innovation, and design, similar to a high-end editorial style."""
+Description: Provide a luxurious, detailed description focusing on the craftsmanship, innovation, and design, in a style similar to high-end editorials."""
 
         # Tokenize input and generate description
         inputs = tokenizer(input_text, return_tensors="pt", max_length=512, truncation=True)
         outputs = model.generate(
             **inputs,
-            max_length=150,  # Limit output to 100-150 words
+            max_length=150,  # Output length 100-150 words
             num_return_sequences=1,
             temperature=0.7,
             top_k=50,
             top_p=0.95,
             do_sample=True,
-            repetition_penalty=1.2  # Prevent repetition in descriptions
+            repetition_penalty=1.2  # Prevent repetition
         )
 
         # Decode generated text
         description = tokenizer.decode(outputs[0], skip_special_tokens=True)
 
-        # Display the result
-        st.write("### Generated Description")
+        # Display the final generated description
+        st.write("### Final Generated Description")
         st.write(description)
 else:
     st.warning("Please select a brand.")
 
-# Add some information about the app
+# Sidebar information
 st.sidebar.title("About")
 st.sidebar.info(
     "This app uses a fine-tuned AI model to generate descriptions for watches. "
     "Select a brand and a watch to get started. The model will generate a unique "
-    "description based on the watch's attributes and additional details."
+    "description based on the watch's attributes and additional details from the Ethos website."
 )
 
-# Add a footer
+# Footer
 st.markdown(
     """
     <style>