Update app.py

app.py

@@ -55,7 +55,7 @@ def display_dti():
         if smiles:
             mol = Chem.MolFromSmiles(smiles)
             mol_img = Chem.Draw.MolToImage(mol)
-            st.image(mol_img, width = 140)
+            st.image(mol_img) #, width = 140)
             
             selected_encoder = st.selectbox(
                 'Select encoder for drug compound',('None', 'CDDD', 'MolBERT')
@@ -65,7 +65,6 @@ def display_dti():
                 CDDD_MODEL_DIR = 'checkpoints/CDDD/default_model'
                 cddd_model = InferenceModel(CDDD_MODEL_DIR)
                 embedding = cddd_model.seq_to_emb([smiles])
-                st.write(f'CDDD embedding: {embedding}')
             elif selected_encoder == 'MolBERT':
                 from molbert.utils.featurizer.molbert_featurizer import MolBertFeaturizer
                 MOLBERT_MODEL_DIR = 'checkpoints/MolBert/molbert_100epochs/checkpoints/last.ckpt'
@@ -73,13 +72,17 @@ def display_dti():
                 embedding = molbert_model.transform([smiles])
             else: 
                 st.write('No pre-trained version of HyperPCM is available for the chosen encoder.')
+                 embedding = None
+            if embedding is not None:
+                st.write(f'{selected_encoder} embedding')
+                st.write(embedding)
 
     with col2:
         st.markdown('### Target')
         sequence = st.text_input('Enter the amino-acid sequence of the query protein target', value='HXHVWPVQDAKARFSEFLDACITEGPQIVSRRGAEEAVLVPIGEWRRLQAAA', placeholder='HXHVWPVQDAKARFSEFLDACITEGPQIVSRRGAEEAVLVPIGEWRRLQAAA')
         
         if sequence:
-            st.write('Plot of protein to be added soon.')
+            st.markdown('\n\n\n\n Plot of protein to be added soon. \n\n\n\n')
             
             selected_encoder = st.selectbox(
                 'Select encoder for protein target',('None', 'SeqVec', 'UniRep', 'ESM-1b', 'ProtT5')
@@ -107,9 +110,10 @@ def display_dti():
                 embedding = encoder.reduce_per_protein(embedding)
             else: 
                 st.write('No pre-trained version of HyperPCM is available for the chosen encoder.')
-                embeddning = None
+                embedding = None
             if embedding is not None:
-                st.write(f'{selected_encoder} embedding: {embedding}')
+                st.write(f'{selected_encoder} embedding')
+                st.write(embedding)
 
 
 def display_protein():