Update app.py

app.py

@@ -1,4 +1,28 @@
-import streamlit as st
+!pip install pyarabic
+!pip install farasapy
+!git clone https://github.com/aub-mind/arabert
 
-x = st.slider('Select a value')
-st.write(x, 'squared is', x * x)
+from arabert.preprocess import ArabertPreprocessor
+from transformers import EncoderDecoderModel, AutoTokenizer
+tokenizer = AutoTokenizer.from_pretrained("tareknaous/bert2bert-empathetic-response-msa")
+model = EncoderDecoderModel.from_pretrained("tareknaous/bert2bert-empathetic-response-msa")
+model.to("cuda")
+model.eval()
+arabert_prep = ArabertPreprocessor(model_name="bert-base-arabert", keep_emojis=False)
+def generate_response(text):
+  text_clean = arabert_prep.preprocess(text)
+  inputs = tokenizer.encode_plus(text_clean,return_tensors='pt')
+  outputs = model.generate(input_ids = inputs.input_ids.to("cuda"),
+                   attention_mask = inputs.attention_mask.to("cuda"),
+                   do_sample = True,
+                   min_length=10,
+                   top_k = 0,
+                   top_p = 0.9,
+                   temperature = 0.5)
+  preds = tokenizer.batch_decode(outputs) 
+  response = str(preds)
+  response = response.replace("\'", '')
+  response = response.replace("[[CLS]", '')
+  response = response.replace("[SEP]]", '')
+  response = str(arabert_prep.desegment(response))
+  return response