| 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"): |
| out = inference(user_input) |
| scores_df = pd.DataFrame([scores], index=['Score']) |
| st.table(scored_df) |
| st.write(out) |
