import streamlit as st
from utils import model_prediction
import requests

# set the page config
st.set_page_config(page_title="Sentence Correction", page_icon="📝", layout="centered")

# set the title
st.title("Sentence Correction")

user_input=st.text_area("Enter text: ")
if st.button("Remove Error: "):
    response=model_prediction(text=user_input)
    st.error(f"Original Text: {user_input}")
    st.success(f"Model Prediction: {response}")

# if st.button("Remove Error"):
#     with st.status("Hitting the api please wait...."):
#         try:
#             response=requests.post("http://localhost:8000/predict", json={"text": user_input})
#             if response.status_code == 200:
#                 result = response.json()
#                 st.error(f"Original Text: {result['original_text']}")
#                 st.success(f"Model Prediction: {result['corrected_text']}")
#                 # st.json(result)
#             else:
#                 st.error("Error in fetching prediction from the API.")
#         except Exception as e:
#             st.write(f"There should be some issue in the api serving {e}")