from smolagents import CodeAgent, DuckDuckGoSearchTool, HfApiModel, load_tool, 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) -> tuple[pd.DataFrame, str]:
    """
    Scrapes Amazon search results for product titles, prices, delivery fees, and links.
    
    Arguments:
        search_url (str): The URL of the Amazon search results page.
    
    Returns:
        tuple[pd.DataFrame, str]: A tuple containing a sorted Pandas DataFrame of products and a recommendation string.
    """
    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 None, "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"])
    
    # Convert to DataFrame for better visualization
    df = pd.DataFrame(product_data)
    
    # Recommendation logic
    best_deal = df.iloc[0] if not df.empty 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 df, 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()