DeepAcceptor / app.py
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import streamlit as st
import pandas as pd
import rdkit
import streamlit_ketcher
from streamlit_ketcher import st_ketcher
import abcBERT
# Page setup
st.set_page_config(page_title="DeepAcceptor", page_icon="πŸ”‹", layout="wide")
st.title("DeepAcceptor")
# Connect to the Google Sheet
url1 = r"https://docs.google.com/spreadsheets/d/1YOEIg0nMTSPkAOr8wkqxQRLuUhys3-J0I-KPEpmzPLw/gviz/tq?tqx=out:csv&sheet=accept"
url = r"https://docs.google.com/spreadsheets/d/1YOEIg0nMTSPkAOr8wkqxQRLuUhys3-J0I-KPEpmzPLw/gviz/tq?tqx=out:csv&sheet=111"
df1 = pd.read_csv(url1, dtype=str, encoding='utf-8')
text_search = st.text_input("Search papers or molecules", value="")
m1 = df1["name"].str.contains(text_search)
m2 = df1["reference"].str.contains(text_search)
df_search = df1[m1 | m2]
if text_search:
st.write(df_search)
st.download_button( "Download edited files as .csv", df_search.to_csv(), "df_search.csv", use_container_width=True)
edited_df = st.data_editor(df1, num_rows="dynamic")
edited_df.to_csv(url)
st.download_button(
"⬇️ Download edited files as .csv", edited_df.to_csv(), "edited_df.csv", use_container_width=True
)
molecule = st.text_input("Molecule")
smile_code = st_ketcher(molecule)
st.markdown(f"Smile code: ``{smile_code}``")
try:
pce = abcBERT.main( str(smile_code ) )
st.markdown(f"PCE: ``{pce}``")
except:
st.markdown(f"PCE: None ")