Update app.py

app.py

@@ -79,18 +79,19 @@ st.markdown("Examples of rare diseases include [**Fellman syndrome**](https://ra
 st.markdown("A full list of rare diseases tracked by GARD can be found [here](https://rarediseases.info.nih.gov/diseases/browse-by-first-letter).")
 
 if disease_or_gard_id:
-  df = extract_abs.streamlit_extraction(disease_or_gard_id, max_results, filtering,
-                                        NER_pipeline, entity_classes, 
-                                        extract_diseases,GARD_dict, max_length, 
-                                        classify_model_vars)
-  st.dataframe(df, height=100)
-  csv = convert_df(df)
-  st.download_button(
-     label="Download epidemiology results for "+disease_or_gard_id+" as CSV",
-     data=df.to_csv().encode('utf-8'),
-     file_name=disease_or_gard_id+'.csv',
-     mime='text/csv',
- )
-  #st.dataframe(data=None, width=None, height=None)
-  
+    df, sankey_data = extract_abs.streamlit_extraction(disease_or_gard_id, max_results, filtering,
+                                NER_pipeline, entity_classes, 
+                                extract_diseases,GARD_dict, max_length, 
+                                classify_model_vars)
+    st.dataframe(df, height=100)
+    csv = convert_df(df)
+        st.download_button(
+        label="Download epidemiology results for "+disease_or_gard_id+" as CSV",
+        data=df.to_csv().encode('utf-8'),
+        file_name=disease_or_gard_id+'.csv',
+        mime='text/csv',
+        )
+    #st.dataframe(data=None, width=None, height=None)
+    gathered, relevant, epidemiologic = sankey_data
+    
 # st.code(body, language="python")