Upload app.py

app.py

@@ -223,9 +223,24 @@ def load_model():
     except Exception as e:
         logger.error(f"Error loading model: {e}")
         return f"Error loading model: {e}"
-def models_ready():
-    return all([gemma_model, gemma_tokenizer, classifier_model, classifier_tokenizer])
-    
+        
+def models_ready() -> bool:
+    ready = all(x is not None for x in [
+        gemma_model, gemma_tokenizer, classifier_model, classifier_tokenizer
+    ])
+    if not ready:
+        logger.warning(
+            "models_ready=False  gemma_model=%s gemma_tok=%s phi_model=%s phi_tok=%s",
+            type(gemma_model).__name__ if gemma_model is not None else None,
+            type(gemma_tokenizer).__name__ if gemma_tokenizer is not None else None,
+            type(classifier_model).__name__ if classifier_model is not None else None,
+            type(classifier_tokenizer).__name__ if classifier_tokenizer is not None else None,
+        )
+    return ready
+
+# Load model on startup
+msg = load_model()
+logger.info("load_model(): %s", msg)
     
     
 # ===================================================================
@@ -375,8 +390,7 @@ def classify_solution(question: str, solution: str):
         
         
 
-# Load model on startup
-load_model()
+
 
 # Create Gradio interface
 with gr.Blocks(title="Math Solution Classifier", theme=gr.themes.Soft()) as app: