| from parrot import Parrot | |
| import torch | |
| import warnings | |
| warnings.filterwarnings("ignore") | |
| #import nltk #next stage, when executing multiple sentences | |
| import streamlit as st | |
| # ''' | |
| # uncomment to get reproducable paraphrase generations | |
| # def random_state(seed): | |
| # torch.manual_seed(seed) | |
| # if torch.cuda.is_available(): | |
| # torch.cuda.manual_seed_all(seed) | |
| # random_state(1234) | |
| # ''' | |
| # #Init models (make sure you init ONLY once if you integrate this to your code) | |
| def load_model(): | |
| # Fetch & load model | |
| parrot = Parrot(model_tag="prithivida/parrot_paraphraser_on_T5") | |
| return parrot | |
| parrot = load_model() | |
| st.title("Let's Rewrite your sentence!") | |
| input_phrase = st.text_input("Input your text here:") | |
| option = st.selectbox('Do you want to preserve some of the original words?', | |
| ('Yes', 'No')) | |
| if option == 'Yes': | |
| oc = False | |
| else: | |
| oc= True | |
| if st.button('Submit Text!'): | |
| st.header(':blue[Input]') | |
| st.write(f" {input_phrase}") | |
| st.text("--"*30) | |
| st.header(':blue[Output]') | |
| output_phrases = parrot.augment(input_phrase=input_phrase,do_diverse=oc) | |
| if output_phrases is not None: | |
| for phrases in output_phrases: | |
| score = phrases[1] | |
| sentence = phrases[0] | |
| if score > 0: | |
| st.write(sentence) | |
| else: | |
| st.write("Sorry! No sentences were found with a good score!") | |
| else: | |
| st.write("Sorry! No sentences were found with a good score!") | |
| st.header("Feedback") | |
| st.write("[Kindly consider providing feedback!](https://forms.gle/97st7g2n9NNpqnXw5)") |