Update app.py

app.py

@@ -1,18 +1,15 @@
-from smolagents import CodeAgent, DuckDuckGoSearchTool, HfApiModel, load_tool, tool
+from smolagents import tool
 import requests
 from bs4 import BeautifulSoup
-import pandas as pd
-import yaml
-from tools.final_answer import FinalAnswerTool
 
 @tool
 def amazon_product_scraper(search_url: str) -> list:
     """
-    A tool that scrapes Amazon search results for product titles, prices, delivery fees, and links.
-    
+    Scrapes Amazon search results for product titles, prices, delivery fees, and links.
+
     Args:
-        search_url (str): The URL of the Amazon search results page. This should be a valid Amazon search URL containing product listings.
-    
+        search_url (str): The URL of the Amazon search results page containing product listings.
+
     Returns:
         list: A list containing two elements:
             - A list of dictionaries, each with keys "Title", "Price", "Delivery", "Link", sorted by price.
@@ -21,67 +18,41 @@ def amazon_product_scraper(search_url: str) -> list:
     headers = {
         "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/119.0.0.0 Safari/537.36"
     }
-    
+
     response = requests.get(search_url, headers=headers)
     if response.status_code != 200:
         return [], "Failed to retrieve Amazon results. Amazon may be blocking requests."
-    
+
     soup = BeautifulSoup(response.text, 'html.parser')
-    
+
     product_data = []
-    
+
     for item in soup.select("div[data-asin]"):
         title_tag = item.select_one("h2 a")
         price_tag = item.select_one("span.a-price-whole")
         delivery_tag = item.select_one("span.s-align-children-center")
-        
+
         if title_tag and price_tag:
             title = title_tag.text.strip()
             price = price_tag.text.strip().replace(',', '')  # Normalize prices
             delivery = delivery_tag.text.strip() if delivery_tag else "Free"
             link = "https://www.amazon.com" + title_tag["href"]
-            
+
             product_data.append({
                 "Title": title,
                 "Price": float(price) if price.isnumeric() else None,
                 "Delivery": delivery,
                 "Link": link
             })
-    
+
     # Filter out products with no price and sort by price
     product_data = [p for p in product_data if p["Price"] is not None]
     product_data.sort(key=lambda x: x["Price"])
-    
+
     # Recommendation logic
     best_deal = product_data[0] if product_data else None
     recommendation = ""
     if best_deal is not None:
         recommendation = f"Best deal: {best_deal['Title']} at ${best_deal['Price']} with {best_deal['Delivery']} (Link: {best_deal['Link']})"
-    
-    return product_data, recommendation
 
-# Define the Agent
-final_answer = FinalAnswerTool()
-model = HfApiModel(
-    max_tokens=2096,
-    temperature=0.5,
-    model_id='Qwen/Qwen2.5-Coder-32B-Instruct',
-    custom_role_conversions=None,
-)
-
-with open("prompts.yaml", 'r') as stream:
-    prompt_templates = yaml.safe_load(stream)
-    
-agent = CodeAgent(
-    model=model,
-    tools=[final_answer, amazon_product_scraper], # Adding the scraper tool
-    max_steps=6,
-    verbosity_level=1,
-    grammar=None,
-    planning_interval=None,
-    name=None,
-    description=None,
-    prompt_templates=prompt_templates
-)
-
-GradioUI(agent).launch()
+    return product_data, recommendation