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#!/usr/bin/env python3
"""
Web Search Tool for GAIA Agent System
Handles web searches using DuckDuckGo and content extraction from URLs
"""
import re
import logging
import time
from typing import Dict, List, Optional, Any
from urllib.parse import urlparse, urljoin
import requests
from bs4 import BeautifulSoup
from duckduckgo_search import DDGS
from tools import BaseTool
logger = logging.getLogger(__name__)
class WebSearchResult:
"""Container for web search results"""
def __init__(self, title: str, url: str, snippet: str, content: str = ""):
self.title = title
self.url = url
self.snippet = snippet
self.content = content
def to_dict(self) -> Dict[str, str]:
return {
"title": self.title,
"url": self.url,
"snippet": self.snippet,
"content": self.content[:1500] + "..." if len(self.content) > 1500 else self.content
}
class WebSearchTool(BaseTool):
"""
Web search tool using DuckDuckGo
Handles searches, URL content extraction, and result filtering
"""
def __init__(self):
super().__init__("web_search")
# Configure requests session for web scraping
self.session = requests.Session()
self.session.headers.update({
'User-Agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36'
})
self.session.timeout = 10
def _execute_impl(self, input_data: Any, **kwargs) -> Dict[str, Any]:
"""
Execute web search operations based on input type
Args:
input_data: Can be:
- str: Search query or URL to extract content from
- dict: {"query": str, "action": str, "limit": int, "extract_content": bool}
"""
if isinstance(input_data, str):
# Handle both search queries and URLs
if self._is_url(input_data):
return self._extract_content_from_url(input_data)
else:
return self._search_web(input_data)
elif isinstance(input_data, dict):
query = input_data.get("query", "")
action = input_data.get("action", "search")
limit = input_data.get("limit", 5)
extract_content = input_data.get("extract_content", False)
if action == "search":
return self._search_web(query, limit, extract_content)
elif action == "extract":
return self._extract_content_from_url(query)
else:
raise ValueError(f"Unknown action: {action}")
else:
raise ValueError(f"Unsupported input type: {type(input_data)}")
def _is_url(self, text: str) -> bool:
"""Check if text is a URL"""
return bool(re.match(r'https?://', text))
def _search_web(self, query: str, limit: int = 5, extract_content: bool = False) -> Dict[str, Any]:
"""
Search the web using DuckDuckGo with enhanced rate limiting handling
"""
for attempt in range(3):
try:
logger.info(f"Searching web for: {query} (attempt {attempt + 1}/3)")
# Progressive delays to handle rate limiting
if attempt > 0:
delay = 5 * (2 ** (attempt - 1)) # 5s, 10s delays
logger.info(f"Waiting {delay}s before retry due to rate limiting...")
time.sleep(delay)
with DDGS() as ddgs:
# Use DuckDuckGo search with proper parameters
search_results = list(ddgs.text(
keywords=query,
max_results=limit,
region='us-en',
safesearch='moderate'
))
if not search_results:
if attempt < 2:
logger.warning(f"No results on attempt {attempt + 1}, retrying...")
continue
else:
return {
"query": query,
"found": False,
"message": "No web search results found after retries",
"results": []
}
results = []
for result in search_results:
try:
web_result = WebSearchResult(
title=result.get('title', 'No title'),
url=result.get('href', ''),
snippet=result.get('body', 'No description')
)
# Optionally extract full content from each URL
if extract_content and web_result.url:
try:
content_result = self._extract_content_from_url(web_result.url)
if content_result.get('found'):
web_result.content = content_result['content'][:1000] # Limit content size
except Exception as e:
logger.warning(f"Failed to extract content from {web_result.url}: {e}")
# Continue without content extraction rather than failing
results.append(web_result.to_dict())
except Exception as result_error:
logger.warning(f"Error processing search result: {result_error}")
# Continue with other results rather than failing entire search
continue
# Return successful results even if some individual results failed
return {
"query": query,
"found": len(results) > 0,
"results": results,
"total_results": len(results),
"message": f"Found {len(results)} web search results"
}
except Exception as e:
error_msg = str(e)
if "ratelimit" in error_msg.lower() or "rate limit" in error_msg.lower() or "403" in error_msg or "202" in error_msg or "429" in error_msg:
logger.warning(f"Web search attempt {attempt + 1} failed: {error_msg}")
if attempt < 2:
continue
else:
logger.error(f"Web search attempt {attempt + 1} failed with non-rate-limit error: {error_msg}")
if attempt < 2:
continue
# If all attempts failed, try fallback search strategy
logger.warning("All DuckDuckGo attempts failed, trying fallback search strategy...")
return self._fallback_search(query)
def _fallback_search(self, query: str) -> Dict[str, Any]:
"""
Fallback search strategy when DuckDuckGo is completely unavailable
"""
try:
# Try a simple Wikipedia search as fallback
import wikipedia
wikipedia.set_lang("en")
# Extract key terms from query for Wikipedia search
search_terms = query.replace("site:", "").strip()
try:
# Search Wikipedia pages
wiki_results = wikipedia.search(search_terms, results=3)
if wiki_results:
fallback_results = []
for i, page_title in enumerate(wiki_results[:2], 1):
try:
page = wikipedia.page(page_title)
summary = page.summary[:200] + "..." if len(page.summary) > 200 else page.summary
web_result = WebSearchResult(
title=f"{page_title} (Wikipedia)",
url=page.url,
snippet=summary
)
fallback_results.append(web_result.to_dict())
except:
continue
if fallback_results:
return {
"query": query,
"found": True,
"results": fallback_results,
"total_results": len(fallback_results),
"message": f"Using Wikipedia fallback search. Found {len(fallback_results)} results"
}
except:
pass
except ImportError:
pass
# Last resort: return a helpful message
return {
"query": query,
"found": False,
"message": "❌ Web search failed due to rate limiting. Please try again later or provide the information directly.",
"results": [],
"error_type": "search_failure"
}
def _extract_content_from_url(self, url: str) -> Dict[str, Any]:
"""
Extract readable content from a web page
"""
try:
logger.info(f"Extracting content from: {url}")
# Get page content
response = self.session.get(url)
response.raise_for_status()
# Parse with BeautifulSoup
soup = BeautifulSoup(response.content, 'html.parser')
# Remove script and style elements
for script in soup(["script", "style", "nav", "header", "footer", "aside"]):
script.decompose()
# Extract title
title = soup.find('title')
title_text = title.get_text().strip() if title else "No title"
# Extract main content
content = self._extract_main_content(soup)
# Extract metadata
meta_description = ""
meta_desc = soup.find('meta', attrs={'name': 'description'})
if meta_desc:
meta_description = meta_desc.get('content', '')
# Extract links
links = []
for link in soup.find_all('a', href=True)[:10]: # First 10 links
link_url = urljoin(url, link['href'])
link_text = link.get_text().strip()
if link_text and len(link_text) > 5: # Filter out short/empty links
links.append({"text": link_text, "url": link_url})
return {
"url": url,
"found": True,
"title": title_text,
"content": content,
"meta_description": meta_description,
"links": links,
"content_length": len(content),
"message": "Successfully extracted content from URL"
}
except requests.exceptions.RequestException as e:
return {
"url": url,
"found": False,
"message": f"Failed to fetch URL: {str(e)}",
"error_type": "network_error"
}
except Exception as e:
return {
"url": url,
"found": False,
"message": f"Failed to extract content: {str(e)}",
"error_type": "parsing_error"
}
def _extract_main_content(self, soup: BeautifulSoup) -> str:
"""
Extract main content from HTML using various strategies
"""
content_parts = []
# Strategy 1: Look for article/main tags
main_content = soup.find(['article', 'main'])
if main_content:
content_parts.append(main_content.get_text())
# Strategy 2: Look for content in common div classes
content_selectors = [
'div.content',
'div.article-content',
'div.post-content',
'div.entry-content',
'div.main-content',
'div#content',
'div.text'
]
for selector in content_selectors:
elements = soup.select(selector)
for element in elements:
content_parts.append(element.get_text())
# Strategy 3: Look for paragraphs in body
if not content_parts:
paragraphs = soup.find_all('p')
for p in paragraphs[:20]: # First 20 paragraphs
text = p.get_text().strip()
if len(text) > 50: # Filter out short paragraphs
content_parts.append(text)
# Clean and combine content
combined_content = '\n\n'.join(content_parts)
# Clean up whitespace and formatting
combined_content = re.sub(r'\n\s*\n', '\n\n', combined_content) # Multiple newlines
combined_content = re.sub(r' +', ' ', combined_content) # Multiple spaces
return combined_content.strip()[:5000] # Limit to 5000 characters
def search_youtube_metadata(self, query: str) -> Dict[str, Any]:
"""
Specialized search for YouTube video information
"""
try:
# Search specifically for YouTube videos
youtube_query = f"site:youtube.com {query}"
with DDGS() as ddgs:
search_results = list(ddgs.text(
keywords=youtube_query,
max_results=3,
region='us-en',
safesearch='moderate'
))
youtube_results = []
for result in search_results:
if 'youtube.com/watch' in result.get('href', ''):
video_id = self._extract_youtube_id(result['href'])
youtube_result = {
"title": result.get('title', 'No title'),
"url": result.get('href', ''),
"description": result.get('body', 'No description'),
"video_id": video_id
}
youtube_results.append(youtube_result)
return {
"query": query,
"found": len(youtube_results) > 0,
"results": youtube_results,
"message": f"Found {len(youtube_results)} YouTube videos"
}
except Exception as e:
raise Exception(f"YouTube search failed: {str(e)}")
def _extract_youtube_id(self, url: str) -> str:
"""Extract YouTube video ID from URL"""
patterns = [
r'(?:v=|\/)([0-9A-Za-z_-]{11}).*',
r'(?:embed\/)([0-9A-Za-z_-]{11})',
r'(?:youtu\.be\/)([0-9A-Za-z_-]{11})'
]
for pattern in patterns:
match = re.search(pattern, url)
if match:
return match.group(1)
return ""
def test_web_search_tool():
"""Test the web search tool with various queries"""
tool = WebSearchTool()
# Test cases
test_cases = [
"Python programming tutorial",
"https://en.wikipedia.org/wiki/Machine_learning",
{"query": "artificial intelligence news", "action": "search", "limit": 3},
{"query": "https://www.python.org", "action": "extract"},
{"query": "OpenAI ChatGPT", "action": "search", "limit": 2, "extract_content": True}
]
print("🧪 Testing Web Search Tool...")
for i, test_case in enumerate(test_cases, 1):
print(f"\n--- Test {i}: {test_case} ---")
try:
result = tool.execute(test_case)
if result.success:
print(f"✅ Success: {result.result.get('message', 'No message')}")
if result.result.get('found'):
if 'results' in result.result:
print(f" Found {len(result.result['results'])} results")
# Show first result details
if result.result['results']:
first_result = result.result['results'][0]
print(f" First result: {first_result.get('title', 'No title')}")
print(f" URL: {first_result.get('url', 'No URL')}")
elif 'content' in result.result:
print(f" Extracted {len(result.result['content'])} characters")
print(f" Title: {result.result.get('title', 'No title')}")
else:
print(f" Not found: {result.result.get('message', 'Unknown error')}")
else:
print(f"❌ Error: {result.error}")
print(f" Execution time: {result.execution_time:.2f}s")
except Exception as e:
print(f"❌ Exception: {str(e)}")
if __name__ == "__main__":
# Test when run directly
test_web_search_tool()