| import pandas as pd | |
| import streamlit as st | |
| from elemeta.nlp.metafeature_extractors_runner import ( | |
| MetafeatureExtractorsRunner, | |
| intensive_metrics, | |
| non_intensive_metrics, | |
| ) | |
| metadata_extractor_runner = MetafeatureExtractorsRunner(non_intensive_metrics + intensive_metrics) | |
| txt = st.text_input('Enter some text 👇', 'I Love Elemeta!') | |
| if txt: | |
| features = metadata_extractor_runner.run(txt) | |
| features = pd.DataFrame([features]).T | |
| features = features.rename(columns={0: 'value'}) | |
| features.index.name = 'feature' | |
| st.write('Features:') | |
| st.dataframe(features, height=1000, use_container_width=True) | |