"""
Metadata Collector - Handles collection and formatting of outline metadata.

Collects source mapping stats, grounding insights, and research coverage.
"""

from typing import Dict, Any, List
from loguru import logger


class MetadataCollector:
    """Handles collection and formatting of various metadata types for UI display."""
    
    def __init__(self):
        """Initialize the metadata collector."""
        pass
    
    def collect_source_mapping_stats(self, mapped_sections, research):
        """Collect source mapping statistics for UI display."""
        from models.blog_models import SourceMappingStats
        
        total_sources = len(research.sources)
        total_mapped = sum(len(section.references) for section in mapped_sections)
        coverage_percentage = (total_mapped / total_sources * 100) if total_sources > 0 else 0.0
        
        # Calculate average relevance score (simplified)
        all_relevance_scores = []
        for section in mapped_sections:
            for ref in section.references:
                if hasattr(ref, 'credibility_score') and ref.credibility_score:
                    all_relevance_scores.append(ref.credibility_score)
        
        average_relevance = sum(all_relevance_scores) / len(all_relevance_scores) if all_relevance_scores else 0.0
        high_confidence_mappings = sum(1 for score in all_relevance_scores if score >= 0.8)
        
        return SourceMappingStats(
            total_sources_mapped=total_mapped,
            coverage_percentage=round(coverage_percentage, 1),
            average_relevance_score=round(average_relevance, 3),
            high_confidence_mappings=high_confidence_mappings
        )
    
    def collect_grounding_insights(self, grounding_insights):
        """Collect grounding insights for UI display."""
        from models.blog_models import GroundingInsights
        
        return GroundingInsights(
            confidence_analysis=grounding_insights.get('confidence_analysis'),
            authority_analysis=grounding_insights.get('authority_analysis'),
            temporal_analysis=grounding_insights.get('temporal_analysis'),
            content_relationships=grounding_insights.get('content_relationships'),
            citation_insights=grounding_insights.get('citation_insights'),
            search_intent_insights=grounding_insights.get('search_intent_insights'),
            quality_indicators=grounding_insights.get('quality_indicators')
        )
    
    def collect_research_coverage(self, research):
        """Collect research coverage metrics for UI display."""
        from models.blog_models import ResearchCoverage
        
        sources_utilized = len(research.sources)
        content_gaps = research.keyword_analysis.get('content_gaps', [])
        competitive_advantages = research.competitor_analysis.get('competitive_advantages', [])
        
        return ResearchCoverage(
            sources_utilized=sources_utilized,
            content_gaps_identified=len(content_gaps),
            competitive_advantages=competitive_advantages[:5]  # Limit to top 5
        )