Update app.py

app.py

@@ -23,11 +23,11 @@ from pdfminer.high_level import extract_text
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 nltk.download('punkt')
 
-def pdf_to_text(PDF, Percent):
+def pdf_to_text(PDF, Min):
    model_name = 'nlpaueb/legal-bert-base-uncased'
    # The setup of huggingface.co
    file_obj = PDF
-   n = int(Percent.replace('%', ''))
+   #n = int(Percent.replace('%', ''))
    tokenizer = AutoTokenizer.from_pretrained("facebook/bart-large-cnn")
    
    model = AutoModelForSeq2SeqLM.from_pretrained("facebook/bart-large-cnn")
@@ -36,10 +36,9 @@ def pdf_to_text(PDF, Percent):
    
    inputs = tokenizer([text], max_length=1024, return_tensors="pt")
    
-   more= (n)/100
-   less = (n-10)/100
+
    # Generate Summary
-   summary_ids = model.generate(inputs["input_ids"], num_beams=2, min_length= less, max_length= more)
+   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]