OpenEdu MCP Server

""" Article data model for OpenEdu MCP Server. This module defines the Article model for representing educational articles from sources like Wikipedia. """ from dataclasses import dataclass, field from datetime import datetime from typing import Dict, Any, Optional, List import sys from pathlib import Path sys.path.insert(0, str(Path(__file__).parent.parent)) from models.base import BaseModel, EducationalMetadata @dataclass class Article(BaseModel): """Model representing an educational article.""" title: str = "" url: str = "" summary: str = "" content: Optional[str] = None categories: List[str] = field(default_factory=list) last_modified: Optional[datetime] = None language: str = "en" # Educational metadata educational_metadata: EducationalMetadata = field(default_factory=EducationalMetadata) related_topics: List[str] = field(default_factory=list) multimedia_resources: List[str] = field(default_factory=list) # Source information source: str = "wikipedia" source_id: Optional[str] = None def to_dict(self) -> Dict[str, Any]: """Convert to dictionary for serialization.""" return { "title": self.title, "url": self.url, "summary": self.summary, "content": self.content, "categories": self.categories, "last_modified": self.last_modified.isoformat() if self.last_modified else None, "language": self.language, "educational_metadata": self.educational_metadata.to_dict(), "related_topics": self.related_topics, "multimedia_resources": self.multimedia_resources, "source": self.source, "source_id": self.source_id, "created_at": self.created_at.isoformat(), "updated_at": self.updated_at.isoformat() } @classmethod def from_dict(cls, data: Dict[str, Any]) -> 'Article': """Create from dictionary.""" educational_metadata = EducationalMetadata.from_dict( data.get("educational_metadata", {}) ) return cls( title=data["title"], url=data["url"], summary=data["summary"], content=data.get("content"), categories=data.get("categories", []), last_modified=datetime.fromisoformat(data["last_modified"]) if data.get("last_modified") else None, language=data.get("language", "en"), educational_metadata=educational_metadata, related_topics=data.get("related_topics", []), multimedia_resources=data.get("multimedia_resources", []), source=data.get("source", "wikipedia"), source_id=data.get("source_id"), created_at=datetime.fromisoformat(data.get("created_at", datetime.now().isoformat())), updated_at=datetime.fromisoformat(data.get("updated_at", datetime.now().isoformat())) ) @classmethod def from_wikipedia(cls, wp_data: Dict[str, Any]) -> 'Article': """Create Article from Wikipedia API response.""" title = wp_data.get("title", "") # Extract summary - handle different response formats summary = "" if "extract" in wp_data: summary = wp_data["extract"] elif "description" in wp_data: summary = wp_data["description"] elif "snippet" in wp_data: # Clean HTML tags from snippet import re snippet = wp_data["snippet"] summary = re.sub(r'<[^>]+>', '', snippet) # Extract URL - handle different response formats url = "" if "content_urls" in wp_data and "desktop" in wp_data["content_urls"]: url = wp_data["content_urls"]["desktop"].get("page", "") elif "fullurl" in wp_data: url = wp_data["fullurl"] elif "url" in wp_data: url = wp_data["url"] elif title: # Construct URL from title lang = wp_data.get("lang", "en") url = f"https://{lang}.wikipedia.org/wiki/{title.replace(' ', '_')}" # Extract last modified last_modified = None if "timestamp" in wp_data: try: # Handle different timestamp formats timestamp = wp_data["timestamp"] if timestamp.endswith("Z"): timestamp = timestamp.replace("Z", "+00:00") last_modified = datetime.fromisoformat(timestamp) except (ValueError, TypeError): pass # Create educational metadata with enhanced analysis educational_metadata = EducationalMetadata() # Combine all text for analysis content_text = f"{title} {summary}".lower() if "extract" in wp_data and wp_data["extract"]: content_text += f" {wp_data['extract']}" # Enhanced educational keyword analysis educational_keywords = { 'basic': ["education", "school", "learning", "teaching", "student"], 'academic': ["academic", "study", "research", "university", "college"], 'subjects': ["science", "mathematics", "history", "literature", "geography"], 'stem': ["biology", "chemistry", "physics", "engineering", "technology"], 'humanities': ["philosophy", "psychology", "sociology", "anthropology", "linguistics"] } relevance_score = 0.0 category_scores = {} for category, keywords in educational_keywords.items(): matches = sum(1 for keyword in keywords if keyword in content_text) if matches > 0: category_scores[category] = matches relevance_score += matches * 0.05 # Boost score for educational categories if "categories" in wp_data: categories_text = " ".join([ cat.replace("Category:", "").lower() if isinstance(cat, str) else cat.get("title", "").replace("Category:", "").lower() for cat in wp_data["categories"] ]) educational_category_keywords = [ "education", "academic", "science", "mathematics", "history", "learning", "research", "university", "school" ] for keyword in educational_category_keywords: if keyword in categories_text: relevance_score += 0.1 educational_metadata.educational_relevance_score = min(relevance_score, 1.0) # Extract and clean categories categories = [] if "categories" in wp_data: for cat in wp_data["categories"]: if isinstance(cat, dict): cat_title = cat.get("title", "").replace("Category:", "") elif isinstance(cat, str): cat_title = cat.replace("Category:", "") else: continue if cat_title and cat_title not in categories: categories.append(cat_title) # Extract content - handle different formats content = wp_data.get("extract", "") if not content and "content" in wp_data: content = wp_data["content"] # Extract multimedia resources multimedia_resources = [] if "thumbnail" in wp_data and wp_data["thumbnail"].get("source"): multimedia_resources.append(wp_data["thumbnail"]["source"]) # Extract related topics from links related_topics = [] if "links" in wp_data: related_topics = wp_data["links"][:10] # Limit to first 10 return cls( title=title, url=url, summary=summary, content=content, categories=categories, last_modified=last_modified, language=wp_data.get("lang", "en"), educational_metadata=educational_metadata, related_topics=related_topics, multimedia_resources=multimedia_resources, source="wikipedia", source_id=str(wp_data.get("pageid", "")) ) def get_word_count(self) -> int: """Get approximate word count of the article.""" text = self.summary if self.content: text += " " + self.content return len(text.split()) def is_suitable_for_reading_level(self, max_words: int = 1000) -> bool: """Check if article is suitable for a specific reading level based on length.""" return self.get_word_count() <= max_words def has_multimedia(self) -> bool: """Check if article has multimedia resources.""" return len(self.multimedia_resources) > 0 def get_educational_score(self) -> float: """Calculate educational relevance score.""" score = self.educational_metadata.educational_relevance_score # Boost score based on educational indicators if self.educational_metadata.grade_levels: score += 0.2 if self.educational_metadata.curriculum_alignment: score += 0.3 if self.categories: score += 0.1 if self.related_topics: score += 0.1 if self.multimedia_resources: score += 0.1 return min(score, 1.0) # Cap at 1.0