from typing import Dict, List, Any import requests from bs4 import BeautifulSoup from duckduckgo_search import DDGS from transformers import pipeline from langchain_community.embeddings import HuggingFaceEmbeddings import time import json import os from urllib.parse import urlparse import logging import random logger = logging.getLogger(__name__) class SearchResult: def __init__(self, title: str, link: str, snippet: str): self.title = title self.link = link self.snippet = snippet class ModelManager: """Manages different AI models for specific tasks""" def __init__(self): self.device = "cpu" self.models = {} self.load_models() def load_models(self): # Use smaller models for CPU deployment self.models['summarizer'] = pipeline( "summarization", model="facebook/bart-base", device=self.device ) self.models['embeddings'] = HuggingFaceEmbeddings( model_name="sentence-transformers/all-MiniLM-L6-v2", model_kwargs={"device": self.device} ) class ContentProcessor: """Processes and analyzes different types of content""" def __init__(self): self.model_manager = ModelManager() def process_content(self, content: str) -> Dict: """Process content and generate insights""" try: # Generate summary summary = self.model_manager.models['summarizer']( content[:1024], max_length=100, min_length=30, do_sample=False )[0]['summary_text'] return { 'summary': summary, 'content': content } except Exception as e: return { 'summary': f"Error processing content: {str(e)}", 'content': content } class WebSearchEngine: """Main search engine class""" def __init__(self): self.processor = ContentProcessor() self.session = requests.Session() self.request_delay = 2.0 self.last_request_time = 0 self.max_retries = 3 self.ddgs = None self.headers = { 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36' } self.initialize_search() def initialize_search(self): """Initialize DuckDuckGo search with retries""" for _ in range(self.max_retries): try: self.ddgs = DDGS() return except Exception as e: logger.error(f"Error initializing DDGS: {str(e)}") time.sleep(random.uniform(1, 3)) raise Exception("Failed to initialize DuckDuckGo search after multiple attempts") def safe_get(self, url: str, max_retries: int = 3) -> requests.Response: """Make a GET request with retries and error handling""" for i in range(max_retries): try: # Add delay between requests current_time = time.time() time_since_last = current_time - self.last_request_time if time_since_last < self.request_delay: time.sleep(self.request_delay - time_since_last + random.uniform(0.5, 1.5)) response = self.session.get(url, headers=self.headers, timeout=10) self.last_request_time = time.time() if response.status_code == 200: return response elif response.status_code == 429: # Rate limit wait_time = (i + 1) * 5 time.sleep(wait_time) continue else: response.raise_for_status() except Exception as e: if i == max_retries - 1: raise time.sleep((i + 1) * 2) raise Exception(f"Failed to fetch URL after {max_retries} attempts") def is_valid_url(self, url: str) -> bool: """Check if URL is valid for crawling""" try: parsed = urlparse(url) return bool(parsed.netloc and parsed.scheme) except: return False def get_metadata(self, soup: BeautifulSoup) -> Dict: """Extract metadata from page""" title = soup.title.string if soup.title else "No title" description = "" if soup.find("meta", attrs={"name": "description"}): description = soup.find("meta", attrs={"name": "description"}).get("content", "") return { 'title': title, 'description': description } def process_url(self, url: str) -> Dict: """Process a single URL""" if not self.is_valid_url(url): return {'error': f"Invalid URL: {url}"} try: response = self.safe_get(url) soup = BeautifulSoup(response.text, 'lxml') # Extract text content for script in soup(["script", "style"]): script.decompose() text = soup.get_text() lines = (line.strip() for line in text.splitlines()) chunks = (phrase.strip() for line in lines for phrase in line.split(" ")) content = ' '.join(chunk for chunk in chunks if chunk) # Get metadata metadata = self.get_metadata(soup) # Process content processed = self.processor.process_content(content) return { 'url': url, 'title': metadata['title'], 'description': metadata['description'], 'summary': processed['summary'], 'content': processed['content'] } except Exception as e: return {'error': f"Error processing {url}: {str(e)}"} def search(self, query: str, max_results: int = 5) -> Dict: """Perform search and process results""" try: # Initialize search if needed if self.ddgs is None: self.initialize_search() # Add delay before search time.sleep(random.uniform(1, 2)) # Search using DuckDuckGo with retries search_results = [] retry_count = 0 while retry_count < self.max_retries and len(search_results) < max_results: try: # Try different regions if search fails regions = ['wt-wt', 'us-en', 'uk-en'] for region in regions: if len(search_results) >= max_results: break results_gen = self.ddgs.text( query, region=region, max_results=max_results - len(search_results) ) for result in results_gen: if len(search_results) >= max_results: break if result and isinstance(result, dict) and 'link' in result: search_results.append(result) time.sleep(random.uniform(0.2, 0.5)) if search_results: break if search_results: break except Exception as e: retry_count += 1 if retry_count >= self.max_retries: logger.error(f"Search failed after {self.max_retries} attempts: {str(e)}") if not search_results: return {'error': f"Search failed after {self.max_retries} attempts: {str(e)}"} break logger.warning(f"Search attempt {retry_count} failed: {str(e)}") time.sleep(random.uniform(2, 5)) self.initialize_search() if not search_results: return {'error': 'No results found'} results = [] for result in search_results: if 'link' in result: processed = self.process_url(result['link']) if 'error' not in processed: results.append(processed) time.sleep(random.uniform(0.5, 1.0)) if not results: return {'error': 'Failed to process any search results'} # Generate insights from results all_content = " ".join([r['summary'] for r in results if 'summary' in r]) return { 'results': results, 'insights': all_content[:1000] if all_content else "No insights available.", 'follow_up_questions': [ f"What are the key differences between {query} and related topics?", f"Can you explain {query} in simple terms?", f"What are the latest developments in {query}?" ] } except Exception as e: return {'error': f"Search failed: {str(e)}"} # Main search function def search(query: str, max_results: int = 5) -> Dict: """Main search function""" engine = WebSearchEngine() return engine.search(query, max_results)