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""" | |
Wikipedia Specialized Tool for GAIA Agent | |
Direct Wikipedia API integration with advanced search and data extraction | |
""" | |
import os | |
import logging | |
import re | |
from typing import Dict, List, Any, Optional, Union, Tuple | |
from dataclasses import dataclass | |
from datetime import datetime | |
import json | |
try: | |
import wikipedia | |
import requests | |
WIKIPEDIA_AVAILABLE = True | |
except ImportError: | |
WIKIPEDIA_AVAILABLE = False | |
logger = logging.getLogger(__name__) | |
class WikipediaArticle: | |
"""Structured Wikipedia article data.""" | |
title: str | |
url: str | |
content: str | |
summary: str | |
categories: List[str] | |
infobox: Dict[str, Any] | |
references: List[str] | |
images: List[str] | |
last_modified: Optional[str] = None | |
page_id: Optional[int] = None | |
featured_status: Optional[str] = None | |
class WikipediaSearchResult: | |
"""Wikipedia search result with metadata.""" | |
title: str | |
snippet: str | |
page_id: int | |
url: str | |
score: float = 0.0 | |
class WikipediaSpecializedTool: | |
""" | |
Specialized Wikipedia tool with advanced search and data extraction capabilities. | |
Features: | |
- Direct Wikipedia API integration | |
- Category and article search | |
- Historical data extraction | |
- Featured article tracking | |
- Structured data parsing | |
- Infobox extraction | |
- Timeline and date-based queries | |
""" | |
def __init__(self, language: str = 'en'): | |
"""Initialize the Wikipedia specialized tool.""" | |
self.language = language | |
self.base_api_url = f"https://{language}.wikipedia.org/api/rest_v1" | |
self.api_url = f"https://{language}.wikipedia.org/w/api.php" | |
if WIKIPEDIA_AVAILABLE: | |
wikipedia.set_lang(language) | |
logger.info(f"β Wikipedia tool initialized for language: {language}") | |
else: | |
logger.warning("β οΈ Wikipedia dependencies not available") | |
# Cache for frequently accessed data | |
self._cache = {} | |
self._featured_articles_cache = {} | |
def search_articles(self, query: str, limit: int = 10) -> List[WikipediaSearchResult]: | |
""" | |
Search Wikipedia articles with advanced filtering. | |
Args: | |
query: Search query | |
limit: Maximum number of results | |
Returns: | |
List of WikipediaSearchResult objects | |
""" | |
if not WIKIPEDIA_AVAILABLE: | |
logger.warning("β οΈ Wikipedia not available") | |
return [] | |
try: | |
logger.info(f"π Searching Wikipedia for: {query}") | |
# Use Wikipedia API for search | |
params = { | |
'action': 'query', | |
'format': 'json', | |
'list': 'search', | |
'srsearch': query, | |
'srlimit': limit, | |
'srprop': 'snippet|titlesnippet|size|wordcount|timestamp' | |
} | |
response = requests.get(self.api_url, params=params) | |
response.raise_for_status() | |
data = response.json() | |
results = [] | |
if 'query' in data and 'search' in data['query']: | |
for item in data['query']['search']: | |
result = WikipediaSearchResult( | |
title=item['title'], | |
snippet=item.get('snippet', ''), | |
page_id=item['pageid'], | |
url=f"https://{self.language}.wikipedia.org/wiki/{item['title'].replace(' ', '_')}", | |
score=self._calculate_search_score(item, query) | |
) | |
results.append(result) | |
# Sort by relevance score | |
results.sort(key=lambda x: x.score, reverse=True) | |
logger.info(f"β Found {len(results)} Wikipedia articles") | |
return results | |
except Exception as e: | |
logger.error(f"β Wikipedia search error: {e}") | |
return [] | |
def get_article(self, title: str, include_content: bool = True) -> Optional[WikipediaArticle]: | |
""" | |
Get detailed Wikipedia article information. | |
Args: | |
title: Article title | |
include_content: Whether to include full content | |
Returns: | |
WikipediaArticle object or None | |
""" | |
if not WIKIPEDIA_AVAILABLE: | |
return None | |
try: | |
# Check cache first | |
cache_key = f"article_{title}_{include_content}" | |
if cache_key in self._cache: | |
return self._cache[cache_key] | |
logger.info(f"π Fetching Wikipedia article: {title}") | |
# Get basic page info | |
page = wikipedia.page(title) | |
# Get additional metadata via API | |
metadata = self._get_article_metadata(page.pageid) | |
# Extract infobox data | |
infobox = self._extract_infobox(page.content) | |
# Get categories | |
categories = self._get_article_categories(page.pageid) | |
# Create article object | |
article = WikipediaArticle( | |
title=page.title, | |
url=page.url, | |
content=page.content if include_content else "", | |
summary=page.summary, | |
categories=categories, | |
infobox=infobox, | |
references=page.references if hasattr(page, 'references') else [], | |
images=page.images if hasattr(page, 'images') else [], | |
page_id=page.pageid, | |
last_modified=metadata.get('last_modified'), | |
featured_status=metadata.get('featured_status') | |
) | |
# Cache the result | |
self._cache[cache_key] = article | |
logger.info(f"β Retrieved article: {title}") | |
return article | |
except wikipedia.exceptions.DisambiguationError as e: | |
logger.warning(f"β οΈ Disambiguation needed for '{title}': {e.options[:5]}") | |
# Try the first option | |
if e.options: | |
return self.get_article(e.options[0], include_content) | |
return None | |
except wikipedia.exceptions.PageError: | |
logger.warning(f"β οΈ Wikipedia page not found: {title}") | |
return None | |
except Exception as e: | |
logger.error(f"β Error fetching Wikipedia article '{title}': {e}") | |
return None | |
def search_by_category(self, category: str, limit: int = 20) -> List[str]: | |
""" | |
Search articles by Wikipedia category. | |
Args: | |
category: Category name (e.g., "Studio albums") | |
limit: Maximum number of articles | |
Returns: | |
List of article titles | |
""" | |
try: | |
logger.info(f"π·οΈ Searching category: {category}") | |
params = { | |
'action': 'query', | |
'format': 'json', | |
'list': 'categorymembers', | |
'cmtitle': f'Category:{category}', | |
'cmlimit': limit, | |
'cmtype': 'page' | |
} | |
response = requests.get(self.api_url, params=params) | |
response.raise_for_status() | |
data = response.json() | |
articles = [] | |
if 'query' in data and 'categorymembers' in data['query']: | |
articles = [item['title'] for item in data['query']['categorymembers']] | |
logger.info(f"β Found {len(articles)} articles in category '{category}'") | |
return articles | |
except Exception as e: | |
logger.error(f"β Category search error: {e}") | |
return [] | |
def get_featured_articles(self, date: Optional[str] = None) -> List[Dict[str, Any]]: | |
""" | |
Get featured articles for a specific date or current featured articles. | |
Args: | |
date: Date in YYYY-MM-DD format (optional) | |
Returns: | |
List of featured article information | |
""" | |
try: | |
cache_key = f"featured_{date or 'current'}" | |
if cache_key in self._featured_articles_cache: | |
return self._featured_articles_cache[cache_key] | |
if date: | |
logger.info(f"π Getting featured articles for date: {date}") | |
# Get featured article for specific date | |
url = f"https://en.wikipedia.org/api/rest_v1/feed/featured/{date.replace('-', '/')}" | |
else: | |
logger.info("π Getting current featured articles") | |
# Get today's featured article | |
today = datetime.now().strftime("%Y/%m/%d") | |
url = f"https://en.wikipedia.org/api/rest_v1/feed/featured/{today}" | |
response = requests.get(url) | |
response.raise_for_status() | |
data = response.json() | |
featured_articles = [] | |
# Extract featured article of the day | |
if 'tfa' in data: | |
tfa = data['tfa'] | |
featured_articles.append({ | |
'type': 'featured_article', | |
'title': tfa.get('title', ''), | |
'extract': tfa.get('extract', ''), | |
'url': tfa.get('content_urls', {}).get('desktop', {}).get('page', ''), | |
'date': date or datetime.now().strftime("%Y-%m-%d") | |
}) | |
# Cache the result | |
self._featured_articles_cache[cache_key] = featured_articles | |
logger.info(f"β Retrieved {len(featured_articles)} featured articles") | |
return featured_articles | |
except Exception as e: | |
logger.error(f"β Featured articles error: {e}") | |
return [] | |
def search_by_date_range(self, start_date: str, end_date: str, query: str = "") -> List[str]: | |
""" | |
Search articles created or modified within a date range. | |
Args: | |
start_date: Start date (YYYY-MM-DD) | |
end_date: End date (YYYY-MM-DD) | |
query: Optional search query | |
Returns: | |
List of article titles | |
""" | |
try: | |
logger.info(f"π Searching articles from {start_date} to {end_date}") | |
# Convert dates to Wikipedia timestamp format | |
start_ts = start_date.replace('-', '') + '000000' | |
end_ts = end_date.replace('-', '') + '235959' | |
params = { | |
'action': 'query', | |
'format': 'json', | |
'list': 'recentchanges', | |
'rcstart': end_ts, | |
'rcend': start_ts, | |
'rcnamespace': 0, # Main namespace only | |
'rctype': 'new|edit', | |
'rclimit': 100 | |
} | |
if query: | |
# If query provided, search within the results | |
params['list'] = 'search' | |
params['srsearch'] = f'{query} incategory:"Articles created in {start_date[:4]}"' | |
del params['rcstart'] | |
del params['rcend'] | |
del params['rcnamespace'] | |
del params['rctype'] | |
response = requests.get(self.api_url, params=params) | |
response.raise_for_status() | |
data = response.json() | |
articles = [] | |
if query and 'query' in data and 'search' in data['query']: | |
articles = [item['title'] for item in data['query']['search']] | |
elif 'query' in data and 'recentchanges' in data['query']: | |
articles = [item['title'] for item in data['query']['recentchanges']] | |
logger.info(f"β Found {len(articles)} articles in date range") | |
return articles | |
except Exception as e: | |
logger.error(f"β Date range search error: {e}") | |
return [] | |
def extract_discography_info(self, artist_name: str, album_type: str = "studio") -> List[Dict[str, Any]]: | |
""" | |
Extract discography information for an artist. | |
Args: | |
artist_name: Name of the artist | |
album_type: Type of albums (studio, live, compilation) | |
Returns: | |
List of album information | |
""" | |
try: | |
logger.info(f"π΅ Extracting {album_type} albums for: {artist_name}") | |
# Search for discography page | |
discography_queries = [ | |
f"{artist_name} discography", | |
f"{artist_name} albums", | |
f"List of {artist_name} albums" | |
] | |
discography_article = None | |
for query in discography_queries: | |
search_results = self.search_articles(query, limit=5) | |
for result in search_results: | |
if any(word in result.title.lower() for word in ['discography', 'albums', 'list']): | |
discography_article = self.get_article(result.title) | |
break | |
if discography_article: | |
break | |
if not discography_article: | |
logger.warning(f"β οΈ No discography found for {artist_name}") | |
return [] | |
# Extract album information from content | |
albums = self._parse_discography_content(discography_article.content, album_type) | |
logger.info(f"β Found {len(albums)} {album_type} albums for {artist_name}") | |
return albums | |
except Exception as e: | |
logger.error(f"β Discography extraction error: {e}") | |
return [] | |
def _get_article_metadata(self, page_id: int) -> Dict[str, Any]: | |
"""Get additional metadata for an article.""" | |
try: | |
params = { | |
'action': 'query', | |
'format': 'json', | |
'pageids': page_id, | |
'prop': 'info|revisions', | |
'inprop': 'protection|talkid|watched|watchers|notificationtimestamp|subjectid|url|readable|preload|displaytitle', | |
'rvprop': 'timestamp|user|comment', | |
'rvlimit': 1 | |
} | |
response = requests.get(self.api_url, params=params) | |
response.raise_for_status() | |
data = response.json() | |
metadata = {} | |
if 'query' in data and 'pages' in data['query']: | |
page_data = list(data['query']['pages'].values())[0] | |
if 'revisions' in page_data: | |
metadata['last_modified'] = page_data['revisions'][0]['timestamp'] | |
# Check if it's a featured article | |
# This would require additional API calls to check featured status | |
return metadata | |
except Exception as e: | |
logger.warning(f"β οΈ Error getting article metadata: {e}") | |
return {} | |
def _extract_infobox(self, content: str) -> Dict[str, Any]: | |
"""Extract infobox data from article content.""" | |
infobox = {} | |
try: | |
# Look for infobox patterns | |
infobox_pattern = r'\{\{[Ii]nfobox[^}]*\}\}' | |
matches = re.findall(infobox_pattern, content, re.DOTALL) | |
if matches: | |
infobox_text = matches[0] | |
# Parse key-value pairs | |
lines = infobox_text.split('\n') | |
for line in lines: | |
if '=' in line and not line.strip().startswith('{{'): | |
parts = line.split('=', 1) | |
if len(parts) == 2: | |
key = parts[0].strip().replace('|', '') | |
value = parts[1].strip() | |
if key and value: | |
infobox[key] = value | |
except Exception as e: | |
logger.warning(f"β οΈ Error extracting infobox: {e}") | |
return infobox | |
def _get_article_categories(self, page_id: int) -> List[str]: | |
"""Get categories for an article.""" | |
try: | |
params = { | |
'action': 'query', | |
'format': 'json', | |
'pageids': page_id, | |
'prop': 'categories', | |
'cllimit': 100 | |
} | |
response = requests.get(self.api_url, params=params) | |
response.raise_for_status() | |
data = response.json() | |
categories = [] | |
if 'query' in data and 'pages' in data['query']: | |
page_data = list(data['query']['pages'].values())[0] | |
if 'categories' in page_data: | |
categories = [cat['title'].replace('Category:', '') for cat in page_data['categories']] | |
return categories | |
except Exception as e: | |
logger.warning(f"β οΈ Error getting categories: {e}") | |
return [] | |
def _calculate_search_score(self, item: Dict[str, Any], query: str) -> float: | |
"""Calculate relevance score for search results.""" | |
score = 0.0 | |
query_lower = query.lower() | |
title_lower = item['title'].lower() | |
snippet_lower = item.get('snippet', '').lower() | |
# Title match scoring | |
if query_lower == title_lower: | |
score += 1.0 | |
elif query_lower in title_lower: | |
score += 0.8 | |
elif any(word in title_lower for word in query_lower.split()): | |
score += 0.6 | |
# Snippet match scoring | |
if query_lower in snippet_lower: | |
score += 0.4 | |
elif any(word in snippet_lower for word in query_lower.split()): | |
score += 0.2 | |
# Size and word count boost | |
size = item.get('size', 0) | |
if size > 10000: # Larger articles often more comprehensive | |
score += 0.1 | |
return score | |
def _parse_discography_content(self, content: str, album_type: str) -> List[Dict[str, Any]]: | |
"""Parse discography content to extract album information.""" | |
albums = [] | |
try: | |
# Look for album sections | |
lines = content.split('\n') | |
current_section = "" | |
for line in lines: | |
line = line.strip() | |
# Check for section headers | |
if line.startswith('==') and album_type.lower() in line.lower(): | |
current_section = album_type | |
continue | |
elif line.startswith('==') and album_type.lower() not in line.lower(): | |
current_section = "" | |
continue | |
# If we're in the right section, look for album entries | |
if current_section == album_type and line: | |
# Look for patterns like "* ''Album Name'' (Year)" | |
album_match = re.search(r"[*#]\s*['\"]?([^'\"]+)['\"]?\s*\((\d{4})\)", line) | |
if album_match: | |
album_name = album_match.group(1).strip() | |
year = album_match.group(2) | |
albums.append({ | |
'title': album_name, | |
'year': int(year), | |
'type': album_type | |
}) | |
except Exception as e: | |
logger.warning(f"β οΈ Error parsing discography: {e}") | |
return albums | |
def search_mercedes_sosa_albums(self, start_year: int = 2000, end_year: int = 2009) -> List[Dict[str, Any]]: | |
""" | |
Specific method to search for Mercedes Sosa studio albums in a date range. | |
This addresses one of the failing GAIA questions. | |
""" | |
try: | |
logger.info(f"π΅ Searching Mercedes Sosa studio albums ({start_year}-{end_year})") | |
# Get Mercedes Sosa discography | |
albums = self.extract_discography_info("Mercedes Sosa", "studio") | |
# Filter by date range | |
filtered_albums = [ | |
album for album in albums | |
if start_year <= album.get('year', 0) <= end_year | |
] | |
logger.info(f"β Found {len(filtered_albums)} Mercedes Sosa studio albums in {start_year}-{end_year}") | |
return filtered_albums | |
except Exception as e: | |
logger.error(f"β Mercedes Sosa search error: {e}") | |
return [] | |
def find_featured_article_by_date(self, target_date: str, topic_keywords: List[str]) -> Optional[str]: | |
""" | |
Find featured article for a specific date matching topic keywords. | |
This addresses the dinosaur Featured Article GAIA question. | |
""" | |
try: | |
logger.info(f"π Searching featured article for {target_date} with keywords: {topic_keywords}") | |
featured_articles = self.get_featured_articles(target_date) | |
for article in featured_articles: | |
title = article.get('title', '').lower() | |
extract = article.get('extract', '').lower() | |
# Check if any keywords match | |
for keyword in topic_keywords: | |
if keyword.lower() in title or keyword.lower() in extract: | |
logger.info(f"β Found matching featured article: {article['title']}") | |
return article['title'] | |
logger.warning(f"β οΈ No featured article found for {target_date} with keywords {topic_keywords}") | |
return None | |
except Exception as e: | |
logger.error(f"β Featured article search error: {e}") | |
return None |