Update app.py

app.py

@@ -1,40 +1,50 @@
 import gradio as gr
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+import torch
 
 model_id = "GannaEslam38/Pegasus-Arxiv-Generator"
 
-print("Loading model...")
-tokenizer = AutoTokenizer.from_pretrained(model_id)
-model = AutoModelForSeq2SeqLM.from_pretrained(model_id)
+print("🔄 Loading Model...")
+try:
+    tokenizer = AutoTokenizer.from_pretrained(model_id)
+    model = AutoModelForSeq2SeqLM.from_pretrained(model_id)
+    print("✅ Model Loaded!")
+except Exception as e:
+    print(f"❌ Error loading model: {e}")
 
 def generate_text(prompt):
-    
-    inputs = tokenizer(prompt, return_tensors="pt", max_length=512, truncation=True)
-    
-   
-    summary_ids = model.generate(
-        inputs["input_ids"],
-        max_length=150,
-        min_length=30,
-        length_penalty=2.0,
-        num_beams=4,
-        early_stopping=True
-    )
-    
-  
-    decoded = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
-    cleaned_text = decoded.replace("<n>", " ").replace(" .", ".").strip()
-    
-    return cleaned_text
-
+    print(f"📩 Input received: {prompt}")
+    try:
+        inputs = tokenizer(prompt, return_tensors="pt", max_length=512, truncation=True)
+        
+        summary_ids = model.generate(
+            inputs["input_ids"],
+            max_length=120,
+            min_length=10,
+            num_beams=1,
+            early_stopping=True
+        )
+        
+        decoded = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
+        cleaned_text = decoded.replace("<n>", " ").replace(" .", ".").strip()
+        
+        return cleaned_text
+        
+    except Exception as e:
+        return f"Error: {str(e)}"
 
 interface = gr.Interface(
     fn=generate_text,
-    inputs=gr.Textbox(lines=5, label="Input Text", placeholder="Write about AI..."),
-    outputs=gr.Textbox(label="Generated Content"),
+    
+    inputs=gr.Textbox(lines=5, label="Input Text", placeholder="Write your topic here..."),
+    
+    outputs=gr.Textbox(lines=10, label="Generated Content"), 
+    
     title="Generative AI Project",
-    description="This model generates academic-style content using fine-tuned Pegasus.",
-    examples=[["Artificial intelligence is transforming the world"]]
+    description="Fine-tuned Pegasus Model.",
+    examples=[["Artificial intelligence is transforming the world"]],
+    cache_examples=False 
 )
 
-interface.launch()
+if __name__ == "__main__":
+    interface.launch()