Create app.py

app.py

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+import streamlit as st
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+import requests
+from bs4 import BeautifulSoup
+import torch
+
+# Load the pretrained model and tokenizer
+MODEL_NAME = "google/flan-t5-large"
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
+model = AutoModelForSeq2SeqLM.from_pretrained(MODEL_NAME)
+
+# Function to generate text description
+def generate_description(input_text):
+    inputs = tokenizer(input_text, return_tensors="pt", max_length=512, truncation=True)
+    outputs = model.generate(inputs["input_ids"], max_length=200)
+    description = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return description
+
+# Function to scrape brand website
+def scrape_brand_website(brand_name, sku):
+    search_url = f"https://www.google.com/search?q={brand_name}+{sku}"
+    headers = {
+        "User-Agent": "Mozilla/5.0"
+    }
+    response = requests.get(search_url, headers=headers)
+    soup = BeautifulSoup(response.text, 'html.parser')
+    
+    # For demonstration, just fetch the first URL (modify as per your requirement)
+    link = soup.find('a')['href']
+    return link
+
+# Streamlit App
+st.title("Watch Description Generator & Brand Scout")
+
+# Inputs for watch details
+brand_name = st.text_input("Enter Brand Name")
+watch_name = st.text_input("Enter Watch Name")
+sku = st.text_input("Enter Watch SKU")
+
+# Button to generate description
+if st.button("Generate Description"):
+    if brand_name and watch_name and sku:
+        # Generate description using the model
+        input_text = f"Watch Name: {watch_name}, Brand: {brand_name}, SKU: {sku}"
+        generated_description = generate_description(input_text)
+        st.write("Generated Description:")
+        st.write(generated_description)
+
+        # Scrape brand website for relevant information
+        st.write("Fetching Brand Website...")
+        brand_link = scrape_brand_website(brand_name, sku)
+        st.write(f"Brand Website: {brand_link}")
+    else:
+        st.warning("Please fill in all fields.")