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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 [] |