Update app.py

app.py

@@ -1,7 +1,5 @@
 import streamlit as st
 import requests
-from bs4 import BeautifulSoup
-import json
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 
 # Load model and tokenizer
@@ -24,22 +22,7 @@ json_url = "https://www.ethoswatches.com/feeds/holbox_ai.json"
 data = load_json_from_url(json_url)
 
 # Extract unique brands
-brands = sorted(list(set([item["brand"] for item in data])))
-
-# 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')
-
-        # 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 from Ethos."
-    except Exception as e:
-        return f"Error fetching details from Ethos: {str(e)}"
+brands = sorted(set(item["brand"] for item in data))
 
 # Streamlit UI
 st.title("Watch Description Generator")
@@ -47,7 +30,6 @@ st.title("Watch Description Generator")
 # Select brand
 selected_brand = st.selectbox("Select a Brand", ["Select"] + brands)
 
-# Filter watches and SKUs by the selected brand
 if selected_brand != "Select":
     watches = [item["name"] for item in data if item["brand"] == selected_brand]
     skus = [item["sku"] for item in data if item["brand"] == selected_brand]
@@ -55,31 +37,14 @@ if selected_brand != "Select":
     selected_sku = st.selectbox("Select SKU (Optional)", ["Select"] + skus)
 
     # Get the selected watch data from the JSON
-    watch_data = None
-    if selected_watch != "Select":
-        watch_data = next((item for item in data if item["name"] == selected_watch), None)
-    elif selected_sku != "Select":
-        watch_data = next((item for item in data if item["sku"] == selected_sku), None)
+    watch_data = next((item for item in data if item["name"] == selected_watch or item["sku"] == selected_sku), None)
 
     if watch_data:
         # Display the image from the JSON
-        image_url = watch_data.get("image", None)
-        if image_url:
+        if image_url := watch_data.get("image"):
             st.image(image_url, caption=f"{watch_data['name']} Image")
 
-        # 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 description
-            ethos_description = scrape_ethos_description(product_link)
-            st.write("### Ethos Product Description (Extracted)")
-            st.write(ethos_description)
-        else:
-            st.warning("No Ethos link available for this SKU.")
-
-        # Generate a watch description based on attributes and scraped content
+        # Attributes without price
         attributes = {
             "brand": watch_data["brand"],
             "name": watch_data.get("name", "Unknown Watch"),
@@ -94,8 +59,8 @@ if selected_brand != "Select":
             "strap_material": watch_data.get("strap_material", "Unknown Strap Material")
         }
 
-        # Combine Ethos description and attributes into a prompt
-input_text = f"""Generate a detailed, luxurious 150-word description for the following watch, focusing on its craftsmanship, innovation, and design. Use a style similar to high-end watch editorials, highlighting the watch's unique features and its appeal to connoisseurs:
+        # Create a detailed description prompt
+        input_text = f"""Generate a detailed 200-word description for the following watch:
 Brand: {attributes['brand']}
 Name: {attributes['name']}
 SKU: {attributes['sku']}
@@ -108,46 +73,44 @@ Power Reserve: {attributes['power_reserve']}
 Dial Color: {attributes['dial_color']}
 Strap Material: {attributes['strap_material']}
 
-Additional details from Ethos:
-{ethos_description}
-
-Description:"""
+Description: Provide a luxurious, detailed description focusing on the craftsmanship, innovation, and design. Highlight the unique features and selling points of this watch. Use vivid language to paint a picture of the watch's appearance and functionality. Discuss how this watch stands out in the {attributes['brand']} collection and why it would appeal to watch enthusiasts."""
 
         # Tokenize input and generate description
-inputs = tokenizer(input_text, return_tensors="pt", max_length=512, truncation=True)
-outputs = model.generate(
-    **inputs,
-    max_length=300,  # Increased to allow for longer descriptions
-    min_length=200,  # Ensure a minimum length
-    num_return_sequences=1,
-    temperature=0.8,  # Slightly increased for more creativity
-    top_k=50,
-    top_p=0.95,
-    do_sample=True,
-    repetition_penalty=1.2,  # Prevent repetition
-    length_penalty=1.5  # Encourage longer outputs
-)
+        inputs = tokenizer(input_text, return_tensors="pt", max_length=512, truncation=True)
+        outputs = model.generate(
+            **inputs,
+            max_length=300,  # Increased to allow for longer descriptions
+            num_return_sequences=1,
+            temperature=0.8,
+            top_k=50,
+            top_p=0.95,
+            do_sample=True,
+            repetition_penalty=1.2,
+            no_repeat_ngram_size=3  # Prevent repetition of 3-gram phrases
+        )
 
         # Decode generated text
         description = tokenizer.decode(outputs[0], skip_special_tokens=True)
 
-        # Display the final generated description
-        st.write("### Final Generated Description")
+        # Display the result
+        st.write("### Generated Description")
         st.write(description)
-    else:
-        st.warning("No data available for the selected watch.")
+
+        # Add word count
+        word_count = len(description.split())
+        st.write(f"Word count: {word_count}")
 else:
     st.warning("Please select a brand.")
 
-# Sidebar information
+# Add some information about the app
 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 from the Ethos website."
+    "description based on the watch's attributes."
 )
 
-# Footer
+# Add a footer
 st.markdown(
     """
     <style>