Update app.py

app.py

@@ -15,9 +15,9 @@ st.subheader('',divider='rainbow')
 url1= r"https://docs.google.com/spreadsheets/d/1AKkZS04VF3osFT36aNHIb4iUbV8D1uNfsldcpHXogj0/gviz/tq?tqx=out:csv&sheet=dap"
 df1 = pd.read_csv(url1, dtype=str, encoding='utf-8')
 col1, col2 = st.columns(2)
-st.subheader("🔍**Search papers or molecules**")
+st.subheader("💗**The donor and acceptor database**")
 with col1:
-	
+	st.caption("🔍**Search papers or molecules**")
 	text_search = st.text_input(label="_", value="",label_visibility="hidden" )
 	m1 = df1["Donor_Name"].str.contains(text_search)
 	m2 = df1["reference"].str.contains(text_search)
@@ -36,6 +36,7 @@ st.download_button(
     "⬇️ Download edited files as .csv", edited_df.to_csv(), "edited_df.csv", use_container_width=True
 )
 #st.subheader("👇 :red[***Select the type of active layer...***]")
+st.subheader("💗**Molecular editor**")
 col3, col4 = st.columns(2)
 with col3:
 	
@@ -48,7 +49,7 @@ with col4:
 		option ="example"
 		molecule = 'O=C(C(C=C(F)C(F)=C1)=C1C/2=C(C#N)/C#N)C2=C/C3=C(CCCCCCCCCCC)C(S4)=C(S3)C5=C4C6=C(N5CC(CC)CCCC)C7=C(C(SC8=C9SC(/C=C%10C(C(C=C(F)C(F)=C%11)=C%11C\%10=C(C#N)C#N)=O)=C8CCCCCCCCCCC)=C9N7CC(CC)CCCC)C%12=NSN=C6%12'
 		do = 'CCCCC(CC)CC1=C(F)C=C(C2=C3C=C(C4=CC=C(C5=C6C(=O)C7=C(CC(CC)CCCC)SC(CC(CC)CCCC)=C7C(=O)C6=C(C6=CC=C(C)S6)S5)S4)SC3=C(C3=CC(F)=C(CC(CC)CCCC)S3)C3=C2SC(C)=C3)S1'
-
+st.subheader("💗**PCE prediction**")
 if option =="🎈Acceptor":
 	st.subheader("👨‍🔬**Input the SMILES of Acceptor Molecule**")
 	molecule = st.text_input("👨‍🔬**Input the SMILES of Acceptor Molecule**", label_visibility="hidden" )
@@ -79,6 +80,7 @@ try:
 except:
     st.subheader(f"⚡**PCE**:  None  ")
 st.subheader(":black[**🧡 High-throughput screening for high-performance D/A pairs**]")
+
 col5, col6 = st.columns(2)
 with col5:
 	uploaded_files = st.file_uploader("Choose a CSV file")