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"""
Web-related tools for the GAIA Agent.
Includes web search, Wikipedia lookup, arXiv search, and webpage fetching.
"""

import os
import re
import requests
from langchain_core.tools import tool
from tavily import TavilyClient
import wikipedia
import arxiv
from dotenv import load_dotenv

load_dotenv()


@tool
def web_search(query: str, include_content: bool = True, max_results: int = 5) -> str:
    """Search the web for current information with full page content.
    
    Use this for facts, news, people, places, events, or anything you need to look up.
    Returns search results WITH full page content, so you can get detailed information directly.
    
    Args:
        query: The search query
        include_content: If True, includes full page content (default: True)
        max_results: Number of results to return (default: 5)
    """
    try:
        client = TavilyClient(api_key=os.getenv("TAVILY_API_KEY"))
        response = client.search(
            query, 
            max_results=max_results,
            include_raw_content=include_content,  # Get full page content
            include_answer=True,  # Get a direct answer if available
        )
        
        output = []
        
        # Include Tavily's direct answer if available
        if response.get("answer"):
            output.append(f"📌 DIRECT ANSWER: {response['answer']}")
            output.append("=" * 50)
        
        results = response.get("results", [])
        if not results:
            return "No search results found."
        
        for i, r in enumerate(results, 1):
            output.append(f"\n[{i}] {r.get('title', 'N/A')}")
            output.append(f"URL: {r.get('url', 'N/A')}")
            output.append(f"Snippet: {r.get('content', 'N/A')}")
            
            # Include full page content if available
            raw_content = r.get('raw_content')
            if raw_content:
                # Truncate to reasonable length per result
                content_preview = raw_content[:3000]
                if len(raw_content) > 3000:
                    content_preview += "\n...[content truncated]"
                output.append(f"\nFull Content:\n{content_preview}")
            output.append("-" * 40)
        
        return "\n".join(output)
    except Exception as e:
        return f"Search error: {str(e)}"


@tool
def wikipedia_lookup(topic: str) -> str:
    """Look up a topic on Wikipedia for detailed encyclopedic information.
    
    Args:
        topic: The topic to look up
    """
    try:
        search_results = wikipedia.search(topic, results=3)
        if not search_results:
            return f"No Wikipedia article found for: {topic}"
        
        try:
            page = wikipedia.page(search_results[0], auto_suggest=False)
            return f"Title: {page.title}\n\nSummary:\n{page.summary[:4000]}"
        except wikipedia.DisambiguationError as e:
            if e.options:
                page = wikipedia.page(e.options[0], auto_suggest=False)
                return f"Title: {page.title}\n\nSummary:\n{page.summary[:4000]}"
            return f"Multiple matches found: {e.options[:5]}"
        except wikipedia.PageError:
            return f"Page not found: {search_results[0]}"
    except Exception as e:
        return f"Wikipedia error: {str(e)}"


@tool
def arxiv_search(query: str, max_results: int = 5) -> str:
    """Search arXiv for academic papers and research articles.
    
    Use this for scientific papers, research, preprints, and academic publications.
    Returns paper titles, authors, abstracts, and arXiv IDs.
    
    Args:
        query: Search query (can include author names, titles, or topics)
        max_results: Maximum number of results to return (default: 5)
    """
    try:
        # Create arXiv client and search
        client = arxiv.Client()
        search = arxiv.Search(
            query=query,
            max_results=max_results,
            sort_by=arxiv.SortCriterion.Relevance
        )
        
        results = list(client.results(search))
        
        if not results:
            return f"No arXiv papers found for: {query}"
        
        output = []
        for i, paper in enumerate(results, 1):
            output.append(f"[{i}] {paper.title}")
            output.append(f"    Authors: {', '.join(a.name for a in paper.authors[:5])}")
            if len(paper.authors) > 5:
                output[-1] += f" et al. ({len(paper.authors)} total)"
            output.append(f"    Published: {paper.published.strftime('%Y-%m-%d')}")
            output.append(f"    arXiv ID: {paper.entry_id.split('/')[-1]}")
            output.append(f"    Categories: {', '.join(paper.categories[:3])}")
            output.append(f"    PDF: {paper.pdf_url}")
            # Truncate abstract to ~500 chars
            abstract = paper.summary.replace('\n', ' ')[:500]
            if len(paper.summary) > 500:
                abstract += "..."
            output.append(f"    Abstract: {abstract}")
            output.append("---")
        
        return "\n".join(output)
    except Exception as e:
        return f"arXiv search error: {str(e)}"


@tool
def webpage_fetch(url: str, extract_links: bool = False) -> str:
    """Fetch and read the content of a webpage URL.
    
    Use this to read the full content of a page from search results.
    After web_search returns URLs, use this tool to get detailed information.
    
    Args:
        url: The URL to fetch (http or https)
        extract_links: If True, also extract and list links found on the page
    """
    try:
        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'
        }
        
        response = requests.get(url, headers=headers, timeout=30)
        response.raise_for_status()
        
        html = response.text
        
        # Try to use BeautifulSoup for better parsing
        try:
            from bs4 import BeautifulSoup
            soup = BeautifulSoup(html, 'html.parser')
            
            # Remove script and style elements
            for element in soup(['script', 'style', 'nav', 'footer', 'header', 'aside']):
                element.decompose()
            
            # Get title
            title = soup.title.string if soup.title else "No title"
            
            # Get main text content
            text = soup.get_text(separator='\n', strip=True)
            
            # Clean up excessive whitespace
            lines = [line.strip() for line in text.splitlines() if line.strip()]
            text = '\n'.join(lines)
            
            # Extract links if requested
            links_text = ""
            if extract_links:
                links = []
                for a in soup.find_all('a', href=True)[:20]:  # Limit to 20 links
                    href = a['href']
                    link_text = a.get_text(strip=True)[:50]
                    if href.startswith('http'):
                        links.append(f"  - {link_text}: {href}")
                if links:
                    links_text = "\n\nLinks found:\n" + "\n".join(links)
            
            # Truncate to reasonable length
            if len(text) > 8000:
                text = text[:8000] + "\n...[truncated]"
            
            return f"Title: {title}\nURL: {url}\n\nContent:\n{text}{links_text}"
            
        except ImportError:
            # Fallback: basic HTML tag stripping without BeautifulSoup
            # Remove script and style content
            html = re.sub(r'<script[^>]*>.*?</script>', '', html, flags=re.DOTALL | re.IGNORECASE)
            html = re.sub(r'<style[^>]*>.*?</style>', '', html, flags=re.DOTALL | re.IGNORECASE)
            
            # Remove HTML tags
            text = re.sub(r'<[^>]+>', ' ', html)
            
            # Decode HTML entities
            import html as html_module
            text = html_module.unescape(text)
            
            # Clean up whitespace
            text = re.sub(r'\s+', ' ', text).strip()
            
            # Truncate
            if len(text) > 8000:
                text = text[:8000] + "...[truncated]"
            
            return f"URL: {url}\n\nContent:\n{text}\n\n(Note: Install beautifulsoup4 for better parsing: pip install beautifulsoup4)"
            
    except requests.exceptions.Timeout:
        return f"Error: Request timed out for URL: {url}"
    except requests.exceptions.HTTPError as e:
        return f"HTTP Error {e.response.status_code}: Could not fetch {url}"
    except Exception as e:
        return f"Error fetching webpage: {str(e)}"