app.py

Startup

app.py

@@ -0,0 +1,43 @@
+import numpy as np
+import pytesseract as pt
+import pdf2image
+from fpdf import FPDF
+import re
+import nltk
+from nltk.tokenize import sent_tokenize
+from nltk.tokenize import word_tokenize
+import os
+import pdfkit
+import yake
+from transformers import AutoTokenizer, AutoModelForPreTraining, AutoModel, AutoConfig
+from summarizer import Summarizer,TransformerSummarizer
+from transformers import pipelines
+nltk.download('punkt')
+
+ 
+model_name = 'nlpaueb/legal-bert-base-uncased'
+
+
+# The setup of huggingface.co
+custom_config = AutoConfig.from_pretrained(model_name)
+custom_config.output_hidden_states=True
+custom_tokenizer = AutoTokenizer.from_pretrained(model_name)
+custom_model = AutoModel.from_pretrained(model_name, config=custom_config)
+bert_legal_model = Summarizer(custom_model=custom_model, custom_tokenizer=custom_tokenizer)
+
+
+def get_response(input_text):
+  output_text= bert_legal_model(input_text,  min_length = 8, ratio = 0.05
+  
+  return output_text
+  
+  
+ 
+iface = gr.Interface(
+    get_response, 
+    "text", 
+    "text"
+   )
+
+if __name__ == "__main__":
+    iface.launch(share=True)