Update app.py

app.py

@@ -15,9 +15,12 @@ import rdkit
 import streamlit as st
 
 st.title('predictproduct-t5')
-st.markdown('#### At this space, you can predict the products of reactions from their inputs.')
-st.markdown('#### The code expects input_data as a string or CSV file that contains an "input" column. The format of the string or contents of the column are like "REACTANT:{reactants of the reaction}CATALYST:{catalysts of the reaction}REAGENT:{reagents of the reaction}SOLVENT:{solvent of the reaction}".')
-st.markdown('#### If there are no catalyst or reagent, fill the blank with a space. And if there are multiple reactants, concatenate them with "."')
+st.markdown('##### At this space, you can predict the products of reactions from their inputs.')
+st.markdown('##### The code expects input_data as a string or CSV file that contains an "input" column. The format of the string or contents of the column are like "REACTANT:{reactants of the reaction}CATALYST:{catalysts of the reaction}REAGENT:{reagents of the reaction}SOLVENT:{solvent of the reaction}".')
+st.markdown('##### If there are no catalyst or reagent, fill the blank with a space. And if there are multiple reactants, concatenate them with "."')
+st.markdown('##### The output contains smiles of predicted products and sum of log-likelihood for each prediction. Predictions are ordered by their log-likelihood.(0th is the most probable product.) "valid compound" is the most probable and valid(can be recognized by RDKit) prediction.')
+
+
 display_text = 'input the reaction smiles (e.g. REACTANT:CNc1nc(SC)ncc1CO.O.O=[Cr](=O)([O-])O[Cr](=O)(=O)[O-].[Na+]CATALYST: REAGENT: SOLVENT:CC(=O)O)'
 
 class CFG():