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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)