Update app.py

app.py

@@ -12,6 +12,7 @@ def process_csv(file):
     try:
         # Read the CSV file
         df = pd.read_csv(file.name)  # Use file.name to get the file path
+        
         # Ensure the CSV has a 'text' column
         if 'text' not in df.columns:
             return "Error: The CSV file must contain a 'text' column."
@@ -25,17 +26,21 @@ def process_csv(file):
         
         # Get predicted classes
         _, predicted_classes = torch.max(outputs.logits, dim=1)
+        
+        # Add predicted classes to the DataFrame
         df['predicted_class'] = predicted_classes.numpy()
         
         # Return the processed DataFrame as a CSV string
-        return df.to_csv(index=False)
+        output_csv = df.to_csv(index=False)
+        
+        return output_csv
     
     except Exception as e:
         return f"Error: {str(e)}"
 
 # Create the Gradio interface
 input_csv = gr.File(label="Upload CSV File")
-output_csv = gr.Textbox(label="Output")
+output_csv = gr.File(label="Download Processed CSV")
 
 demo = gr.Interface(
     fn=process_csv,