from typing import Dict, List
import requests
from bs4 import BeautifulSoup
import aiohttp
import asyncio
import json
from sentence_transformers import SentenceTransformer
import numpy as np
import re

class DynamicRecommender:
    def __init__(self):
        self.headers = {
            'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36'
        }
        self.model = SentenceTransformer('all-mpnet-base-v2')
        
    async def search_amazon(self, query: str) -> List[Dict]:
        """Search Amazon for products"""
        search_url = f"https://www.amazon.in/s?k={query}"
        async with aiohttp.ClientSession() as session:
            async with session.get(search_url, headers=self.headers) as response:
                if response.status == 200:
                    html = await response.text()
                    return self._parse_amazon_results(html)
        return []
    
    async def search_flipkart(self, query: str) -> List[Dict]:
        """Search Flipkart for products"""
        search_url = f"https://www.flipkart.com/search?q={query}"
        async with aiohttp.ClientSession() as session:
            async with session.get(search_url, headers=self.headers) as response:
                if response.status == 200:
                    html = await response.text()
                    return self._parse_flipkart_results(html)
        return []

    def _parse_amazon_results(self, html: str) -> List[Dict]:
        soup = BeautifulSoup(html, 'html.parser')
        products = []
        for item in soup.select('.s-result-item'):
            try:
                name = item.select_one('.a-text-normal')
                price = item.select_one('.a-price-whole')
                if name and price:
                    products.append({
                        'name': name.text.strip(),
                        'price': price.text.strip(),
                        'source': 'Amazon',
                        'url': 'https://amazon.in' + item.select_one('a')['href']
                    })
            except Exception:
                continue
        return products[:5]

    def _parse_flipkart_results(self, html: str) -> List[Dict]:
        soup = BeautifulSoup(html, 'html.parser')
        products = []
        for item in soup.select('._1AtVbE'):
            try:
                name = item.select_one('._4rR01T')
                price = item.select_one('._30jeq3')
                if name and price:
                    products.append({
                        'name': name.text.strip(),
                        'price': price.text.strip(),
                        'source': 'Flipkart',
                        'url': 'https://flipkart.com' + item.select_one('a')['href']
                    })
            except Exception:
                continue
        return products[:5]

    def _extract_keywords(self, text: str) -> List[str]:
        """Extract relevant search keywords from input"""
        age_match = re.search(r'age\s+(\d+)', text.lower())
        age = age_match.group(1) if age_match else None

        interests = []
        if 'software' in text.lower() or 'engineer' in text.lower():
            interests.extend(['programming books', 'tech gadgets'])
        if 'books' in text.lower():
            interests.append('books')
        if 'successful' in text.lower():
            interests.extend(['self help books', 'business books'])

        return [f"{interest} for {age} year old" if age else interest for interest in interests]

    async def get_recommendations(self, text: str) -> Dict:
        """Get personalized recommendations"""
        try:
            keywords = self._extract_keywords(text)
            all_products = []
            
            for keyword in keywords:
                amazon_products = await self.search_amazon(keyword)
                flipkart_products = await self.search_flipkart(keyword)
                all_products.extend(amazon_products + flipkart_products)
            
            # Remove duplicates and sort by relevance
            seen = set()
            unique_products = []
            for product in all_products:
                if product['name'] not in seen:
                    seen.add(product['name'])
                    unique_products.append(product)
            
            return unique_products[:5]
            
        except Exception as e:
            print(f"Error in recommendations: {str(e)}")
            return []