Update app.py

app.py

@@ -339,13 +339,13 @@ def run_diagnosis(
         Idx2labels[i] for i, p in enumerate(probs) if p >= threshold]
 
     explanation_ = "No prediction was made."
-    if predicted_classes not []:
+    if predicted_classes:
         # Load model (cache for speed)
-        if model_key not in MODEL_CACHE:
-          VLM_MODEL_CACHE[model_key]     = pipeline(task  = "image-text-to-text",
+        if vlm_name not in VLM_MODEL_CACHE:
+          VLM_MODEL_CACHE[vlm_name]     = pipeline(task  = "image-text-to-text",
                               model  = VLM_REGISTRY[vlm_name],
                               trust_remote_code = True)
-        VLM_model = VLM_MODEL_CACHE[model_key]
+        VLM_model = VLM_MODEL_CACHE[vlm_name]
 
         formatted_predictions = {label: output_probs[label] for label in predicted_classes}