ALwrity Backend and Frontend - Stability and Error Handling Improvements

backend/services/persona/core_persona/core_persona_service.py

@@ -18,13 +18,24 @@ from services.persona.facebook.facebook_persona_service import FacebookPersonaSe
 class CorePersonaService:
     """Core service for generating writing personas using Gemini AI."""
     
+    _instance = None
+    _initialized = False
+    
+    def __new__(cls):
+        """Implement singleton pattern to prevent multiple initializations."""
+        if cls._instance is None:
+            cls._instance = super(CorePersonaService, cls).__new__(cls)
+        return cls._instance
+    
     def __init__(self):
-        """Initialize the core persona service."""
-        self.data_collector = OnboardingDataCollector()
-        self.prompt_builder = PersonaPromptBuilder()
-        self.linkedin_service = LinkedInPersonaService()
-        self.facebook_service = FacebookPersonaService()
-        logger.info("CorePersonaService initialized")
+        """Initialize the core persona service (only once)."""
+        if not self._initialized:
+            self.data_collector = OnboardingDataCollector()
+            self.prompt_builder = PersonaPromptBuilder()
+            self.linkedin_service = LinkedInPersonaService()
+            self.facebook_service = FacebookPersonaService()
+            logger.debug("CorePersonaService initialized")
+            self._initialized = True
     
     def generate_core_persona(self, onboarding_data: Dict[str, Any]) -> Dict[str, Any]:
         """Generate core writing persona using Gemini structured response."""

backend/services/persona/enhanced_linguistic_analyzer.py

@@ -26,7 +26,7 @@ class EnhancedLinguisticAnalyzer:
             import spacy
             self.nlp = spacy.load("en_core_web_sm")
             self.spacy_available = True
-            logger.info("SUCCESS: spaCy model loaded successfully - Enhanced linguistic analysis available")
+            logger.debug("SUCCESS: spaCy model loaded successfully - Enhanced linguistic analysis available")
         except ImportError as e:
             logger.error(f"ERROR: spaCy is REQUIRED for persona generation. Install with: pip install spacy && python -m spacy download en_core_web_sm")
             raise ImportError("spaCy is required for enhanced persona generation. Install with: pip install spacy && python -m spacy download en_core_web_sm") from e

backend/services/persona/facebook/facebook_persona_service.py

@@ -20,14 +20,25 @@ from services.llm_providers.gemini_provider import gemini_structured_json_respon
 class FacebookPersonaService:
     """Facebook-specific persona generation and optimization service."""
     
+    _instance = None
+    _initialized = False
+    
+    def __new__(cls):
+        """Implement singleton pattern to prevent multiple initializations."""
+        if cls._instance is None:
+            cls._instance = super(FacebookPersonaService, cls).__new__(cls)
+        return cls._instance
+    
     def __init__(self):
-        """Initialize the Facebook persona service."""
-        self.schemas = FacebookPersonaSchema
-        self.constraints = FacebookPersonaConstraints()
-        self.validation = FacebookPersonaValidation()
-        self.optimization = FacebookPersonaOptimization()
-        self.prompts = FacebookPersonaPrompts()
-        logger.info("FacebookPersonaService initialized")
+        """Initialize the Facebook persona service (only once)."""
+        if not self._initialized:
+            self.schemas = FacebookPersonaSchema
+            self.constraints = FacebookPersonaConstraints()
+            self.validation = FacebookPersonaValidation()
+            self.optimization = FacebookPersonaOptimization()
+            self.prompts = FacebookPersonaPrompts()
+            logger.debug("FacebookPersonaService initialized")
+            self._initialized = True
     
     def generate_facebook_persona(self, core_persona: Dict[str, Any], onboarding_data: Dict[str, Any]) -> Dict[str, Any]:
         """

backend/services/persona/linkedin/linkedin_persona_service.py

@@ -14,11 +14,22 @@ from .linkedin_persona_schemas import LinkedInPersonaSchemas
 class LinkedInPersonaService:
     """Service for generating LinkedIn-specific persona adaptations."""
     
+    _instance = None
+    _initialized = False
+    
+    def __new__(cls):
+        """Implement singleton pattern to prevent multiple initializations."""
+        if cls._instance is None:
+            cls._instance = super(LinkedInPersonaService, cls).__new__(cls)
+        return cls._instance
+    
     def __init__(self):
-        """Initialize the LinkedIn persona service."""
-        self.prompts = LinkedInPersonaPrompts()
-        self.schemas = LinkedInPersonaSchemas()
-        logger.info("LinkedInPersonaService initialized")
+        """Initialize the LinkedIn persona service (only once)."""
+        if not self._initialized:
+            self.prompts = LinkedInPersonaPrompts()
+            self.schemas = LinkedInPersonaSchemas()
+            logger.debug("LinkedInPersonaService initialized")
+            self._initialized = True
     
     def generate_linkedin_persona(self, core_persona: Dict[str, Any], onboarding_data: Dict[str, Any]) -> Dict[str, Any]:
         """

backend/services/persona/persona_quality_improver.py

@@ -24,7 +24,7 @@ class PersonaQualityImprover:
     def __init__(self):
         """Initialize the quality improver."""
         self.linguistic_analyzer = EnhancedLinguisticAnalyzer()
-        logger.info("PersonaQualityImprover initialized")
+        logger.debug("PersonaQualityImprover initialized")
     
     def assess_persona_quality_comprehensive(
         self,