import pandas as pd
import streamlit as st
from inference import inference
from inference import DebertaEvaluator

st.title("Essay Scoring")

categories=['cohesion', 'syntax', 'vocabulary', 'phraseology', 'grammar', 'conventions']

initial_scores = {category: '-' for category in categories}
scores_df = pd.DataFrame(initial_scores, index=['Score'])

pd.set_option('display.float_format', lambda x: '%0.1f' % x)

text = "Here is a sample essay."

user_input = st.text_area("Enter your essay here:", value=text)

if st.button("Calculate Scores"):
    scores = inference(user_input)
    scores = [round(score * 2) / 2 for score in scores[0]]
    new_table = {categories[i]: scores[i] for i in range(len(categories))}
    scores_df = pd.DataFrame(new_table, index=['Score'])

# Display the initial scores table
st.table(scores_df)