Base code

backend/services/linkedin/quality_handler.py

@@ -0,0 +1,62 @@
+"""
+Quality Handler for LinkedIn Content Generation
+
+Handles content quality analysis and metrics conversion.
+"""
+
+from typing import Dict, Any, Optional
+from models.linkedin_models import ContentQualityMetrics
+from loguru import logger
+
+
+class QualityHandler:
+    """Handles content quality analysis and metrics conversion."""
+    
+    def __init__(self, quality_analyzer=None):
+        self.quality_analyzer = quality_analyzer
+    
+    def create_quality_metrics(
+        self, 
+        content: str, 
+        sources: list, 
+        industry: str,
+        grounding_enabled: bool = False
+    ) -> Optional[ContentQualityMetrics]:
+        """
+        Create ContentQualityMetrics object from quality analysis.
+        
+        Args:
+            content: Content to analyze
+            sources: Research sources used
+            industry: Target industry
+            grounding_enabled: Whether grounding was used
+            
+        Returns:
+            ContentQualityMetrics object or None if analysis fails
+        """
+        if not grounding_enabled or not self.quality_analyzer:
+            return None
+            
+        try:
+            quality_analysis = self.quality_analyzer.analyze_content_quality(
+                content=content,
+                sources=sources,
+                industry=industry
+            )
+            
+            # Convert the analysis result to ContentQualityMetrics format
+            return ContentQualityMetrics(
+                overall_score=quality_analysis.get('overall_score', 0.0),
+                factual_accuracy=quality_analysis.get('metrics', {}).get('factual_accuracy', 0.0),
+                source_verification=quality_analysis.get('metrics', {}).get('source_verification', 0.0),
+                professional_tone=quality_analysis.get('metrics', {}).get('professional_tone', 0.0),
+                industry_relevance=quality_analysis.get('metrics', {}).get('industry_relevance', 0.0),
+                citation_coverage=quality_analysis.get('metrics', {}).get('citation_coverage', 0.0),
+                content_length=quality_analysis.get('content_length', 0),
+                word_count=quality_analysis.get('word_count', 0),
+                analysis_timestamp=quality_analysis.get('analysis_timestamp', ''),
+                recommendations=quality_analysis.get('recommendations', [])
+            )
+        except Exception as e:
+            logger.warning(f"Quality metrics creation failed: {e}")
+            return None