Update app.py

app.py

@@ -24,20 +24,23 @@ app.add_middleware(
     allow_headers=["*"],
 )
 
-# Load Model (Baked into the Docker image)
-MODEL_DIR = "local_model"
-MODEL_PATH = os.path.join(MODEL_DIR, "pakistani_lid_v3.onnx")
+# 🚨 Use Absolute Path
+MODEL_PATH = "/app/local_model/pakistani_lid_v3.onnx"
+
+logger.info(f"🚀 Attempting to load model from: {MODEL_PATH}")
 
-logger.info("🚀 Loading pre-baked ONNX model...")
 try:
-    # Check if files exist just in case
     if not os.path.exists(MODEL_PATH):
-        raise FileNotFoundError(f"Model not found at {MODEL_PATH}")
+        # List files for debugging in logs if it fails
+        logger.error(f"Files in /app/local_model: {os.listdir('/app/local_model') if os.path.exists('/app/local_model') else 'Dir not found'}")
+        raise FileNotFoundError(f"Model file missing at {MODEL_PATH}")
     
-    session = ort.InferenceSession(MODEL_PATH, providers=['CPUExecutionProvider'])
+    # Load with mmap to save RAM
+    session_options = ort.SessionOptions()
+    session = ort.InferenceSession(MODEL_PATH, sess_options=session_options, providers=['CPUExecutionProvider'])
     logger.info("✅ Engine is LIVE and Ready!")
 except Exception as e:
-    logger.error(f"❌ Failed to load model: {e}")
+    logger.error(f"❌ Initialization Error: {e}")
     raise e
 
 labels = ("balochi", "english", "pashto", "sindhi", "urdu")
@@ -88,6 +91,7 @@ async def predict(file: UploadFile = File(...)):
         os.remove(temp_path)
         return {"success": True, "language": lang.upper(), "confidence": round(conf * 100, 2)}
     except Exception as e:
+        logger.error(f"Inference Error: {e}")
         if os.path.exists(temp_path): os.remove(temp_path)
         return {"success": False, "error": str(e)}