final touches

app.py

@@ -1,7 +1,6 @@
 import streamlit as st
 from trainer import Trainer
 
-
 class DrugGENConfig:
     submodel='CrossLoss'
     act='relu'
@@ -85,7 +84,10 @@ model_configs = {
 
 
 with st.sidebar:
-    st.title("DrugGEN")
+    st.title("DrugGEN: Target Centric De Novo Design of Drug Candidate Molecules with Graph Generative Deep Adversarial Networks")
+    st.write("[![arXiv](https://img.shields.io/badge/arXiv-2302.07868-b31b1b.svg)](https://arxiv.org/abs/2302.07868) [![github-repository](https://img.shields.io/badge/GitHub-black?logo=github)](https://github.com/HUBioDataLab/DrugGEN)")
+
+
     with st.form("model_selection_from"):
 
         model_name = st.radio(
@@ -94,18 +96,19 @@ with st.sidebar:
 
         submitted = st.form_submit_button("Start Computing")
 
-    if submitted:
-
-        st.write(model_name)
-    
-
 
 if submitted:
-    with st.spinner('Creating the trainer class instance...'):
+    with st.spinner(f'Creating the trainer class instance for {model_name}...'):
         trainer = Trainer(model_configs[model_name])
-    with st.spinner('Running inference function (this may take a while) ...'):
+    with st.spinner(f'Running inference function of {model_name} (this may take a while) ...'):
         trainer.inference()
     st.success(f"Success with the inference of {model_name}")
+
+
+    with open(f'experiments/inference/{model_name}/inference_drugs.txt') as f:
+        inference_drugs = f.read()
+    st.download_button(label="Click to download generated molecules", data=inference_drugs, file_name=f'{model_name}_inference.smi', mime="text/plain")
+
 else:
     st.warning("Please select a model to make inference")
 

experiments/.gitignore

@@ -0,0 +1 @@
+inference/