Update app.py

app.py

@@ -115,15 +115,15 @@ loaded.empty()
 st.markdown("Examples of rare diseases include [**Fellman syndrome**](https://rarediseases.info.nih.gov/diseases/1/gracile-syndrome), [**Classic Homocystinuria**](https://rarediseases.info.nih.gov/diseases/6667/classic-homocystinuria), [**7383**](https://rarediseases.info.nih.gov/diseases/7383/phenylketonuria), and [**GARD:0009941**](https://rarediseases.info.nih.gov/diseases/9941/fshmd1a). A full list of rare diseases tracked by the NIH Genetic and Rare Diseases Information Center (GARD) can be found [here](https://rarediseases.info.nih.gov/diseases/browse-by-first-letter).")
 
 if disease_or_gard_id:
-    df, sankey_data, name_gardID = streamlit_extraction(disease_or_gard_id, max_results, filtering,
+    df, sankey_data, disease_gardid = streamlit_extraction(disease_or_gard_id, max_results, filtering,
                                                         epi_extract, rd_identify, extract_diseases, epi_classify)
     #IF it returns something, then continue.
     if sankey_data:
         df.replace(to_replace='None', value="None")
         st.dataframe(df, height=200)
         csv = convert_df(df)
-        disease, gardID = name_gardID
         #if the user input does not have a number in it (i.e. weak proxy for if it is a GARD ID), then preserve the user input as the disease term.
+        disease, gardID = disease_gardid
         if not bool(re.search(r'\d', disease_or_gard_id)):
             disease = disease_or_gard_id
             
@@ -133,10 +133,10 @@ if disease_or_gard_id:
             file_name=disease+'.csv',
             mime='text/csv',
             )
+        if gardID:
+            st.markdown('See the NIH GARD page for ['+disease+'](https://rarediseases.info.nih.gov/diseases/'+str(re.sub('GARD:|0','',gardID))+'/'+str('-'.join(disease.split()))+')')
         
-        st.markdown('See the NIH GARD page for ['+disease+'](https://rarediseases.info.nih.gov/diseases/'+str(re.sub('GARD:|0','',gardID))+'/'+str('-'.join(disease.split()))+')')
-        
-        fig = epi_sankey(sankey_data,disease)
+        fig = epi_sankey(sankey_data, disease)
         st.plotly_chart(fig, use_container_width=True)
         
         if 'IDS' in list(df.columns):