Update app.py

app.py

@@ -73,13 +73,13 @@ def filter_by_frequency(counts_dict: dict, threshold_percent: float = 0.2):
 def simple_predict(text, num_predictions=3):
     """Simple language detection function for Gradio interface"""
     if not text or not text.strip():
-        return "Please enter some text for language detection."
+        return {"error": "Please enter some text for language detection."}
     
     try:
         # Clean the text
         cleaned_lines = list(yield_clean_rows([text]))
         if not cleaned_lines:
-            return "No valid text found after cleaning."
+            return {"error": "No valid text found after cleaning."}
         
         # Get predictions for each line
         all_predictions = []
@@ -88,7 +88,7 @@ def simple_predict(text, num_predictions=3):
             all_predictions.extend(predictions)
         
         if not all_predictions:
-            return "No predictions could be made."
+            return {"error": "No predictions could be made."}
         
         # Group predictions by language
         predictions_by_lang = groupby(get_label, all_predictions)
@@ -108,18 +108,18 @@ def simple_predict(text, num_predictions=3):
         return results
         
     except Exception as e:
-        return f"Error during prediction: {str(e)}"
+        return {"error": f"Error during prediction: {str(e)}"}
 
 def batch_predict(text, threshold_percent=0.2):
     """More advanced prediction with filtering"""
     if not text or not text.strip():
-        return "Please enter some text for language detection."
+        return {"error": "Please enter some text for language detection."}
     
     try:
         # Clean the text
         cleaned_lines = list(yield_clean_rows([text]))
         if not cleaned_lines:
-            return "No valid text found after cleaning."
+            return {"error": "No valid text found after cleaning."}
         
         # Get predictions
         predictions = [model_predict(line) for line in cleaned_lines]
@@ -127,7 +127,7 @@ def batch_predict(text, threshold_percent=0.2):
         predictions = list(concat(predictions))
         
         if not predictions:
-            return "No predictions could be made."
+            return {"error": "No predictions could be made."}
         
         # Group and filter
         predictions_by_lang = groupby(get_label, predictions)
@@ -145,7 +145,7 @@ def batch_predict(text, threshold_percent=0.2):
         return results
         
     except Exception as e:
-        return f"Error during prediction: {str(e)}"
+        return {"error": f"Error during prediction: {str(e)}"}
 
 def build_demo_interface():
     app_title = "Language Detection Tool"