Update app.py

app.py

@@ -1,22 +1,24 @@
 import gradio as gr
 from transformers import pipeline
 
-# Load the summarization model
+# Load your summarization model
 summarizer = pipeline("summarization", model="Curative/t5-summarizer-cnn")
 
-# Define the summarization function
+# Define function for Gradio
 def summarize_text(input_text):
-    summary = summarizer(input_text, max_length=150, min_length=30, do_sample=False)
-    return summary[0]['summary_text']
+    if not input_text.strip():
+        return "Please enter some text to summarize."
+    result = summarizer(input_text, max_length=150, min_length=40, do_sample=False)
+    return result[0]['summary_text']
 
-# Create the Gradio UI
-iface = gr.Interface(
+# Create Gradio interface
+demo = gr.Interface(
     fn=summarize_text,
-    inputs=gr.Textbox(lines=5, placeholder="Enter text to summarize..."),
+    inputs=gr.Textbox(lines=10, placeholder="Enter text to summarize..."),
     outputs="text",
-    title="T5 Text Summarizer",
-    description="Enter a passage, and the T5 model will generate a concise summary."
+    title="T5 Summarizer (CNN/DailyMail)",
+    description="A fine-tuned T5 model for text summarization (based on cnn_dailymail v3.0.0)."
 )
 
-# Launch the app
-iface.launch()
+# Launch app
+demo.launch()