Update app.py

app.py

@@ -16,7 +16,7 @@ import yake
 from zipfile import ZipFile
 from gtts import gTTS
 from transformers import AutoTokenizer, AutoModelForPreTraining, AutoModel, AutoConfig
-from summarizer import Summarizer,TransformerSummarizer
+from summarizer import Summarizer, TransformerSummarizer
 from transformers import pipelines
 from pdfminer.high_level import extract_text
 
@@ -33,47 +33,33 @@ def pdf_to_text(text, PDF):
    if text == "":
       # The setup of huggingface.co
       file_obj = PDF
-      #n = int(Percent.replace('%', ''))
-
       text = extract_text(file_obj.name)
       inputs = tokenizer([text], max_length=1024, return_tensors="pt")
       
       Min = int(Min)
       # Generate Summary
-      summary_ids = model.generate(inputs["input_ids"], num_beams=2,min_length=Min, max_length=Min+1000)
+      summary_ids = model.generate(inputs["input_ids"], num_beams=2, min_length=Min, max_length=Min+1000)
       output_text  = tokenizer.batch_decode(summary_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
     
    else:   
       inputs = tokenizer([text], max_length=1024, return_tensors="pt")      
       # Generate Summary
-      
-      summary_ids = model.generate(inputs["input_ids"], num_beams=2,min_length=Min, max_length=Min+1000)
+      summary_ids = model.generate(inputs["input_ids"], num_beams=2, min_length=Min, max_length=Min+1000)
       output_text  = tokenizer.batch_decode(summary_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
    
-
-   #output_text= bert_legal_model(text,  min_length = 8, ratio = 0.05)
- 
-   
    pdf = FPDF()  
    pdf.add_page()
    pdf.set_font("Times", size = 12)
-  # open the text file in read mode
    f = output_text
-  # insert the texts in pdf
    pdf.multi_cell(190, 10, txt = f, align = 'C')
-  # save the pdf with name .pdf
    pdf.output("legal.pdf")  
      
    myobj = gTTS(text=output_text, lang='en', slow=False)
    myobj.save("legal.wav")
    
-   return  "legal.wav", output_text, "legal.pdf"
-   
+   return "legal.wav", output_text, "legal.pdf"
     
-  #  return path 
-    #pageObject.extractText() 
-iface = gr.Interface(fn = pdf_to_text,
-   inputs =["text", "file"], outputs=["audio","text", "file"] )
+iface = gr.Interface(fn=pdf_to_text, inputs=["text", "file"], outputs=["audio", "text", "file"])
 
 if __name__ == "__main__":
-    iface.launch(share=True)
+    iface.launch()  # Removed 'share=True'