Update app.py

app.py

@@ -11,6 +11,14 @@ import streamlit as st
 st.title("Epidemiology Extraction Pipeline for Rare Diseases")
 st.subheader("National Center for Advancing Translational Sciences (NIH/NCATS)") 
 
+#### CHANGE SIDEBAR WIDTH ###
+st.markdown(f'''
+    <style>
+        section[data-testid="stSidebar"] .css-ng1t4o {{width: 10rem;}}
+        section[data-testid="stSidebar"] .css-1d391kg {{width: 10rem;}}
+    </style>
+''',unsafe_allow_html=True)
+
 #max_results is Maximum number of PubMed ID's to retrieve BEFORE filtering
 max_results = st.sidebar.number_input("Maximum number of articles to find in PubMed", min_value=1, max_value=None, value=50)
 
@@ -26,9 +34,9 @@ with st.spinner('Loading Epidemiology Models and Dependencies...'):
     GARD_dict, max_length = extract_abs.load_GARD_diseases()
 st.success('All Models and Dependencies Loaded!')
 
-GARD_Disease_Id = st.text_input("Input a rare disease term or GARD ID.", value="Fellman syndrome")
+disease_or_gard_id = st.text_input("Input a rare disease term or GARD ID.", value="Fellman syndrome")
 
-if text:
+if disease_or_gard_id:
   df = extract_abs.search_term_extraction(disease_or_gard_id, max_results, filtering,
                                            NER_pipeline, entity_classes, 
                                            extract_diseases,GARD_dict, max_length,