| import pandas as pd | |
| import streamlit as st | |
| from transformers import pipeline | |
| from inference import inference | |
| from inference import DebertaEvaluator | |
| pipe = pipeline('sentiment-analysis') | |
| text = st.text_area('enter some text: ') | |
| 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=[0]) | |
| 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_df = pd.DataFrame([scores], index=['Score']) | |
| st.table(scored_df) | |
| st.write(out) |