Update app.py

app.py

@@ -1,7 +1,6 @@
 from pptx import Presentation
 import re
 from transformers import pipeline
-import subprocess
 import gradio as gr
 
 def extract_text_from_pptx(file_path):
@@ -22,7 +21,7 @@ def predict_pptx_content(file_path):
         cleaned_text = re.sub(r'\s+', ' ', extracted_text)
 
         classifier = pipeline("text-classification", model="Ahmed235/roberta_classification")
-        #summarizer = pipeline("summarization", model="Falconsai/text_summarization")
+        # summarizer = pipeline("summarization", model="Falconsai/text_summarization")
 
         result = classifier(cleaned_text)[0]
         predicted_label = result['label']
@@ -31,29 +30,14 @@ def predict_pptx_content(file_path):
         prediction = {
             "Predicted Label": predicted_label,
             "Evaluation": f"Evaluate the topic according to {predicted_label} is: {predicted_probability}"
-            #"Summary": summarizer(cleaned_text, max_length=80, min_length=30, do_sample=False)
+            # "Summary": summarizer(cleaned_text, max_length=80, min_length=30, do_sample=False)
         }
 
         return prediction
     except Exception as e:
-        print(f"Error processing file: {e}")
-        return {"error": str(e)}
-
-
-    classifier = pipeline("text-classification", model="Ahmed235/roberta_classification")
-    #summarizer = pipeline("summarization", model="Falconsai/text_summarization")
-
-    result = classifier(cleaned_text)[0]
-    predicted_label = result['label']
-    predicted_probability = result['score']
-
-    prediction = {
-        "Predicted Label": predicted_label,
-        "Evaluation": f"Evaluate the topic according to {predicted_label} is: {predicted_probability}"
-        #"Summary": summarizer(cleaned_text, max_length=80, min_length=30, do_sample=False)
-    }
-
-    return prediction
+        error_message = str(e)
+        print(f"Error processing file: {error_message}")
+        return {"error": error_message}
 
 # Define the Gradio interface
 iface = gr.Interface(
@@ -65,4 +49,4 @@ iface = gr.Interface(
 )
 
 # Deploy the Gradio interface
-iface.launch(share=True)
+iface.launch(share=True)