Fix classification errors - improve error handling and debugging

app.py

@@ -14,14 +14,17 @@ class HebrewIntentClassifier:
         model_name = "humy65/hebrew-intent-classifier"
 
         try:
-            print("Loading Hebrew Intent Classification model...")
+            print(f"Loading Hebrew Intent Classification model: {model_name}")
             self.tokenizer = AutoTokenizer.from_pretrained(model_name)
             self.model = AutoModelForSequenceClassification.from_pretrained(
                 model_name)
             self.model.eval()
             print("Model loaded successfully!")
+            print(f"Model labels: {self.model.config.id2label}")
         except Exception as e:
             print(f"Error loading model: {e}")
+            import traceback
+            traceback.print_exc()
             raise e
 
     def predict(self, text):
@@ -59,7 +62,7 @@ class HebrewIntentClassifier:
             # Format results in Hebrew and English
             intent_translations = {
                 "ביטול מנוי": "Cancel Subscription",
-                "שאלה כללית": "General Question",
+                "שאלה כללית": "General Question", 
                 "שכחת סיסמה": "Password Reset",
                 "תמיכה טכנית": "Technical Support"
             }
@@ -67,7 +70,7 @@ class HebrewIntentClassifier:
             result_text = f"""
 🎯 **כוונה חזויה / Predicted Intent:** {predicted_label}
 🎲 **רמת ביטחון / Confidence:** {confidence:.1%}
-🔤 **תרגום / Translation:** {intent_translations.get(predicted_label, "Unknown")}
+🔤 **תרגום / Translation:** {intent_translations.get(predicted_label, predicted_label)}
 
 📊 **כל התחזיות / All Predictions:**
 """
@@ -77,13 +80,16 @@ class HebrewIntentClassifier:
                 all_scores.items(), key=lambda x: x[1], reverse=True)
             for intent, score in sorted_scores:
                 bar = "█" * int(score * 20)
-                translation = intent_translations.get(intent, "Unknown")
+                translation = intent_translations.get(intent, intent)
                 result_text += f"\\n{intent} ({translation}): {score:.1%} {bar}"
 
             return result_text, all_scores, predicted_label
 
         except Exception as e:
-            return f"Error: {str(e)}", {}, "שגיאה"
+            print(f"Prediction error: {e}")
+            import traceback
+            traceback.print_exc()
+            return f"Classification Error: {str(e)}", {}, f"Error: {str(e)}"
 
 
 # Initialize the classifier
@@ -97,7 +103,10 @@ except Exception as e:
 def classify_text(text):
     """Main classification function"""
     if classifier is None:
-        return "Model not loaded properly", {}, "Model Error"
+        return "❌ Model not loaded properly - please check logs", {}, "Model Error"
+    
+    if not text or not text.strip():
+        return "⚠️ Please enter some Hebrew text to classify", {}, "Empty Input"
 
     return classifier.predict(text)
 
@@ -211,8 +220,8 @@ with gr.Blocks(
     - **קוד מקור / Source:** [GitHub Repository](https://github.com/your-repo)
     
     ### 🔗 קישורים / Links
-    - [Model on Hugging Face](https://huggingface.co/Huggingm1r@n/hebrew-intent-classifier)
-    - [Documentation](https://huggingface.co/Huggingm1r@n/hebrew-intent-classifier/blob/main/README.md)
+    - [Model on Hugging Face](https://huggingface.co/humy65/hebrew-intent-classifier)
+    - [Documentation](https://huggingface.co/humy65/hebrew-intent-classifier/blob/main/README.md)
     
     Built with ❤️ using Hugging Face Transformers and Gradio
     """)