Update app.py

app.py

@@ -1,20 +1,14 @@
-import gradio as gr
+from parrot import Parrot
 import torch
-from transformers import PegasusForConditionalGeneration, PegasusTokenizer
 
-model_name = 'tuner007/pegasus_paraphrase'
-torch_device = 'cuda' if torch.cuda.is_available() else 'cpu'
-tokenizer = PegasusTokenizer.from_pretrained(model_name)
-model = PegasusForConditionalGeneration.from_pretrained(model_name).to(torch_device)
-
-def paraphrase_text(input_text, max_length):
-  batch = tokenizer([input_text],truncation=True,padding='longest',max_length=int(max_length), return_tensors="pt").to(torch_device)
-  translated = model.generate(**batch,max_length=int(max_length),num_beams=3, num_return_sequences=3, temperature=1.5)
-  tgt_text = tokenizer.batch_decode(translated, skip_special_tokens=True)
-  return tgt_text[0], tgt_text[1], tgt_text[2]
+parrot = Parrot(model_tag="prithivida/parrot_paraphraser_on_T5", use_gpu=False)
 
+def paraphrase_text(input_text):
+  para_phrases = parrot.augment(input_phrase=phrase, 
+                               max_return_phrases = 3)
+  return para_phrases[0][0], para_phrases[1][0] if para_phrases[1][0] else '' , para_phrases[2][0] if para_phrases[2][0] else ''
 
 examples = [["Begin your professional career by learning data science skills with Data science Dojo, a globally recognized e-learning platform where we teach students how to learn data science, data analytics, machine learning and more.", "45"], ["Hello, I am a paraphrasing tool. How can I help you?", "30"]]
 
-demo = gr.Interface(fn=paraphrase_text, inputs=["text", "text"], outputs=["text", "text", "text"], title="Paraphrase", examples=examples)
+demo = gr.Interface(fn=paraphrase_text, inputs="text", outputs=["text", "text", "text"], title="Paraphrase", examples=examples)
 demo.launch( debug = True )