Update app.py

app.py

@@ -26,10 +26,10 @@ def predict_pptx_content(file_path):
         extracted_text = extract_text_from_pptx(file_path)
         cleaned_text = re.sub(r'\s+', ' ', extracted_text)
         
-        # Limit text length before classification
+        
         limited_text = limit_text_length(cleaned_text)
 
-        # Perform inference using the pipeline
+    
         result = classifier(limited_text)
 
         predicted_label = result[0]['label']
@@ -44,14 +44,14 @@ def predict_pptx_content(file_path):
         
         output_dict = json.dumps(output, indent = 3)
 
-        return {"output": output_dict}  # Return the JSON string within a dictionary
+        return {"output": output_dict}  
 
     except Exception as e:
         # Log the error details
         print(f"Error in predict_pptx_content: {e}")
         return {"error": str(e)}
 
-# Define the Gradio interface
+
 iface = gr.Interface(
     fn=predict_pptx_content,
     inputs=gr.File(type="filepath", label="Upload PowerPoint (.pptx) file"),