.....

core/config.py

@@ -54,7 +54,7 @@ class Settings(BaseSettings):
     ENABLE_AUTO_LANGUAGE_DETECTION: bool = True
     
     # Safety & Compliance
-    ENABLE_RED_FLAG_DETECTION: bool = True
+    # ENABLE_RED_FLAG_DETECTION: bool = True
     REQUIRE_DISCLAIMER: bool = True
     LOG_ANONYMIZATION: bool = True
     

services/ml_service.py

@@ -6,18 +6,16 @@ from services.natlas_service import NATLaSService
 
 class MLService:
     """ML Service with N-ATLaS and embeddings"""
-
+    
     def __init__(self):
         self.embedding_model = None
         self.natlas_service = None
         self.device = "cuda" if torch.cuda.is_available() else "cpu"
-        # Flag to control usage of NATLaS (renamed to avoid shadowing method)
-        self.use_natlas_flag = True
-
+        
     async def initialize(self):
         """Initialize all ML services"""
         print(f"🤖 Initializing ML Services on {self.device}")
-
+        
         # Load embedding model
         print(f"📊 Loading: {settings.EMBEDDING_MODEL}")
         self.embedding_model = SentenceTransformer(
@@ -25,28 +23,28 @@ class MLService:
             device=self.device
         )
         print("✅ Embedding model loaded")
-
+        
         # Initialize N-ATLaS
         self.natlas_service = NATLaSService()
         await self.natlas_service.initialize()
-
+    
     async def generate_embedding(self, text: str, language: Optional[str] = None) -> List[float]:
         """Generate embedding"""
         if self.embedding_model is None:
             raise RuntimeError("Embedding model not initialized")
-
+        
         embedding = self.embedding_model.encode(
             text.strip(),
             convert_to_numpy=True,
             normalize_embeddings=True
         )
         return embedding.tolist()
-
+    
     async def generate_embeddings_batch(self, texts: List[str]) -> List[List[float]]:
         """Generate embeddings in batch"""
         if self.embedding_model is None:
             raise RuntimeError("Embedding model not initialized")
-
+        
         embeddings = self.embedding_model.encode(
             [t.strip() for t in texts],
             convert_to_numpy=True,
@@ -54,26 +52,20 @@ class MLService:
             normalize_embeddings=True
         )
         return embeddings.tolist()
-
+    
     async def analyze_with_natlas(self, symptoms: str, language: str = "en") -> str:
         """Use N-ATLaS for analysis"""
-        if not self.use_natlas_flag:
-            return "N-ATLaS analysis disabled."
-        if self.natlas_service is None:
-            raise RuntimeError("N-ATLaS service not initialized")
         return await self.natlas_service.analyze_symptoms(symptoms, language)
-
+    
     def detect_language(self, text: str) -> str:
         """Detect language"""
-        if self.natlas_service is None:
-            raise RuntimeError("N-ATLaS service not initialized")
         return self.natlas_service.detect_language(text)
-
+    
     def get_model_info(self) -> dict:
         """Get model information"""
         return {
             "embedding_model": settings.EMBEDDING_MODEL,
             "device": self.device,
-            "dimension": self.embedding_model.get_sentence_embedding_dimension() if self.embedding_model else None,
-            "natlas": self.natlas_service.get_model_info() if self.natlas_service else None
-        }
+            "dimension": self.embedding_model.get_sentence_embedding_dimension(),
+            "natlas": self.natlas_service.get_model_info()
+        }