Create app.py

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="🔋", 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  ")