Upload api_app.py

api_app.py

@@ -8,21 +8,16 @@ import os
 
 # --- Setup ---
 app = FastAPI()
-# Define the path where the model files will be located in the deployed environment
-MODEL_PATH = "." # In Hugging Face Spaces, files are often in the root directory
+MODEL_PATH = "." 
+
+# --- CRITICAL CHANGE: REMOVE THE try/except BLOCK TEMPORARILY ---
+# The deployment will crash, but the logs will show the exact reason.
+
+processor = AutoImageProcessor.from_pretrained(MODEL_PATH)
+model = ViTForImageClassification.from_pretrained(MODEL_PATH)
 
-# Load model and processor outside the endpoint for speed
-try:
-    processor = AutoImageProcessor.from_pretrained(MODEL_PATH)
-    model = ViTForImageClassification.from_pretrained(MODEL_PATH)
-except Exception as e:
-    # A fallback/debug print if loading fails during deployment
-    print(f"Error loading model or processor from {MODEL_PATH}: {e}")
-    # You might need to check file names or adjust MODEL_PATH if this fails
-    
 device = "cuda" if torch.cuda.is_available() else "cpu"
 model.to(device)
-model.eval()
 
 # --- Prediction Endpoint ---
 @app.post("/predict")