app.py

import streamlit as st
import transformers
import tensorflow
import PIL
from PIL import Image
import time
from transformers import pipeline

model_checkpoint = "Modfiededition/t5-base-fine-tuned-on-jfleg"


@st.cache(allow_output_mutation=True, suppress_st_warning=True)
def load_model():
    return pipeline("text2text-generation", model=model_checkpoint)
model = load_model()

    
#prompts
st.title("Writing Assistant for you 🦄")
image = Image.open('grammar.jpg').resize((1000,500))
st.image(image, caption='Sunrise by the mountains')
st.subheader("Some examples: ")
example_1 = st.button("I am write on AI")
example_2 = st.button("This sentence has, bads grammar mistake!")

textbox = st.text_area('Write your text in this box:', '', height=100, max_chars=1000)

button = st.button('Detect grammar mistakes:')

my_bar = st.progress(0)
for percent_complete in range(100):
    time.sleep(0.1)
    my_bar.progress(percent_complete + 1)
# output
if example_1:
    output_text = model("I am write on AI")[0]["generated_text"]
    st.markdown("**"+output_text+"**")

if example_2:
    output_text = model("This sentence has, bads grammar mistake!")[0]["generated_text"]
    st.markdown("**"+output_text+"**")
if button:
    output_text = model(textbox)[0]["generated_text"]
    st.markdown("**"+output_text+"**")