Update app.py

app.py

@@ -39,25 +39,25 @@ def predict_relevance(question, answer):
         return "Irrelevant"
 
 #  confidence analysis
-def predict_confidence(question, answer):
-    if not answer.strip():  
+def predict_confidence(question, answer, threshold=0.4):
+    if not isinstance(answer, str) or not answer.strip():  
         return "Not Confident"
 
+    # Tokenize input
     inputs = confidence_tokenizer(question, answer, return_tensors="pt", padding=True, truncation=True)
+    
+    # Set model to evaluation mode
     confidence_model.eval()
 
     with torch.no_grad():
         outputs = confidence_model(**inputs)
         logits = outputs.logits
         probabilities = torch.softmax(logits, dim=-1)
-        
-        print("Logits:", logits)
-        print("Probabilities:", probabilities)
-        
-        confidence_prob = probabilities[0, 1]  # Probability for Confident class
 
-        #  lower threshold
-        return "Confident" if confidence_prob > 0.40 else "Not Confident"
+        confidence_prob = probabilities[0, 1].item()  # Extract probability for "Confident" class
+
+        
+        return "Confident" if confidence_prob > threshold else "Not Confident"
 
 # Questions from questions.py
 def fetch_questions():