Update app.py

app.py

@@ -1,27 +1,22 @@
 import gradio as gr
 from transformers import pipeline
 
-# Load the BART model for summarization
 summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
 
-# Function to summarize text based on the min and max length
 def summarize_text(text, min_length, max_length):
-    # Summarize the input text with the specified min and max length
     summary = summarizer(text, min_length=min_length, max_length=max_length)
     return summary[0]['summary_text']
 
-# Create Gradio Interface
 iface = gr.Interface(
-    fn=summarize_text,  # Function to call for summarization
+    fn=summarize_text, 
     inputs=[
         gr.Textbox(label="Enter Text", placeholder="Type or paste a long text here...", lines=10),
         gr.Slider(minimum=10, maximum=50, step=1, label="Minimum Length", value=10),
         gr.Slider(minimum=50, maximum=150, step=1, label="Maximum Length", value=100),
     ],
     outputs=gr.Textbox(label="Summarized Text"),
-    live=False,  # Disable live preview while typing
+    live=False,  
     description="Text Summarization using BART model. Set minimum and maximum token lengths for the summary."
 )
 
-# Launch the interface
 iface.launch()