Update app.py

app.py

@@ -1,34 +1,34 @@
 import gradio as gr
-from PyPDF2 import PdfReader  
+from PyPDF2 import PdfReader  
 from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
 
-model_name = "ArtifactAI/led_large_16384_arxiv_summarization" 
-model = AutoModelForSeq2SeqLM.from_pretrained(model_name)  
+model_name = "ArtifactAI/led_large_16384_arxiv_summarization" 
+model = AutoModelForSeq2SeqLM.from_pretrained(model_name)  
 tokenizer = AutoTokenizer.from_pretrained(model_name)
 
 def summarize_pdf_abstract(pdf_file):
 
-    try:
-        reader = PdfReader(pdf_file)  
-        abstract_text = ""   
-        for page in reader.pages:
-            if "Abstract" in page.extract_text() or "Introduction" in page.extract_text():
-                abstract_text = page.extract_text()
-                break
-                
-        inputs = tokenizer(abstract_text, return_tensors="pt")
-        outputs = model.generate(**inputs) 
-        summary = tokenizer.decode(outputs[0])          
+  try:
+    reader = PdfReader(pdf_file)  
+    abstract_text = ""  
+    for page in reader.pages:
+      if "Abstract" in page.extract_text() or "Introduction" in page.extract_text():
+        abstract_text = page.extract_text()
+        break
+         
+    inputs = tokenizer(abstract_text, return_tensors="pt")
+    outputs = model.generate(**inputs) 
+    summary = tokenizer.decode(outputs[0])      
 
-        return {"summary": summary}
-    
-    except Exception as e:
-        raise Exception(str(e))
+    return {"summary": summary}
+   
+  except Exception as e:
+    raise Exception(str(e))
 
 interface = gr.Interface(
-    fn=summarize_pdf_abstract, 
-    inputs=gr.inputs.File(label="Upload PDF"),
-    outputs=gr.outputs.Textbox(label="Summary")
+  fn=summarize_pdf_abstract,
+  inputs=[gr.File(label="Upload PDF")],
+  outputs=[gr.Textbox(label="Summary")]
 )
 
-interface.launch(share=True)
+interface.launch(share=True)