Update app.py

app.py

@@ -2,49 +2,59 @@ import gradio as gr
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 import torch
 
+
 model_id = "GannaEslam38/Pegasus-Arxiv-Generator"
 
 print("🔄 Loading Model...")
 try:
     tokenizer = AutoTokenizer.from_pretrained(model_id)
     model = AutoModelForSeq2SeqLM.from_pretrained(model_id)
-    print("✅ Model Loaded!")
+    print("✅ Model Loaded Successfully!")
 except Exception as e:
     print(f"❌ Error loading model: {e}")
 
+
 def generate_text(prompt):
     print(f"📩 Input received: {prompt}")
+    
+    
+    if len(prompt.split()) < 3:
+        return "⚠️ text is too short, please write a full sentence."
+
     try:
         inputs = tokenizer(prompt, return_tensors="pt", max_length=512, truncation=True)
         
+        print("🧠 Generating...")
+        
         summary_ids = model.generate(
             inputs["input_ids"],
-            max_length=120,
+            max_length=100,
             min_length=10,
-            num_beams=1,
-            early_stopping=True
+            num_beams=1,           
+            do_sample=False,        
+            no_repeat_ngram_size=2  
+           
         )
         
         decoded = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
         cleaned_text = decoded.replace("<n>", " ").replace(" .", ".").strip()
         
+        print(f"✅ Output: {cleaned_text}")
         return cleaned_text
         
     except Exception as e:
+        print(f"❌ Error: {e}")
         return f"Error: {str(e)}"
 
+
 interface = gr.Interface(
     fn=generate_text,
-    
-    inputs=gr.Textbox(lines=5, label="Input Text", placeholder="Write your topic here..."),
-    
-    outputs=gr.Textbox(lines=10, label="Generated Content"), 
-    
+    inputs=gr.Textbox(lines=5, label="Input Text", placeholder="Deep learning allows computers to..."),
+    outputs=gr.Textbox(lines=10, label="Generated Content"),
     title="Generative AI Project",
-    description="Fine-tuned Pegasus Model.",
-    examples=[["Artificial intelligence is transforming the world"]],
+    description="Fine-tuned Pegasus Model on ArXiv Papers.",
     cache_examples=False 
 )
 
 if __name__ == "__main__":
-    interface.launch()
+    interface.queue().launch()