Update src/services/cv_service.py

src/services/cv_service.py

@@ -19,38 +19,18 @@ class CVParsingService:
         if not cv_text or not cv_text.strip():
             return self._create_fallback_data()
         
+        logger.info(f"CV text loaded: {len(cv_text)} characters")
         sections = self.orchestrator.split_cv_sections(cv_text)
+        logger.info(f"Sections extracted: {list(sections.keys())}")
         cv_data = self.orchestrator.extract_all_sections(sections)
-        
+        logger.info(f"CV data extracted: {cv_data is not None}")
         if cv_data and cv_data.get("candidat"):
+            logger.info("Calculating scores...")
             scores = self.scoring_agent.calculate_scores(cv_data["candidat"])
             cv_data["candidat"].update(scores)
+            logger.info(f"Scores calculated: {len(scores.get('analyse_competences', []))} skills scored")
+        else:
+            logger.warning("No valid CV data extracted, using fallback")
+            return self._create_fallback_data()
         
-        return cv_data
-    
-    def _create_fallback_data(self) -> Dict[str, Any]:
-        return {
-            "candidat": {
-                "informations_personnelles": {
-                    "nom": "Non spécifié",
-                    "email": "Non spécifié",
-                    "numero_de_telephone": "Non spécifié",
-                    "localisation": "Non spécifiée"
-                },
-                "compétences": {
-                    "hard_skills": [],
-                    "soft_skills": []
-                },
-                "expériences": [],
-                "projets": {
-                    "professional": [],
-                    "personal": []
-                },
-                "formations": [],
-                "reconversion": {
-                    "is_reconversion": False,
-                    "analysis": "Analyse non disponible"
-                },
-                "analyse_competences": []
-            }
-        }
+        return cv_data