Update app.py

app.py

@@ -8,14 +8,14 @@ import extract_abs
 import streamlit as st
 
 ########## Title for the Web App ##########
-st.title("Epidemiology Extraction Pipeline for Rare Diseases by the National Center for Advancing Translational Sciences (NIH/NCATS)")
-
+st.title("Epidemiology Extraction Pipeline for Rare Diseases")
+st.subheader("by the National Center for Advancing Translational Sciences (NIH/NCATS)") 
 #st.header(body, anchor=None)
 #st.subheader(body, anchor=None) 
 #Anchor is for the URL, can be custom str
 
 # https://docs.streamlit.io/library/api-reference/text/st.markdown
-
+'''
 col1, col2 = st.columns(2)
 
 with col1:
@@ -26,7 +26,7 @@ with col2:
     filtering = st.radio("What type of filtering would you like?",('Strict', 'Lenient', 'None'))
     extract_diseases = st.checkbox("Extract Rare Diseases", value=False)
     #max_results is Maximum number of PubMed ID's to retrieve BEFORE filtering
-    max_results = st.sidebar.number_input(label, min_value=1, max_value=None, value=50)
+    max_results = st.number_input("Maximum number of articles to find in PubMed", min_value=1, max_value=None, value=50)
     # https://docs.streamlit.io/library/api-reference/widgets/st.number_input
 
 with col1:
@@ -37,29 +37,43 @@ with col1:
         st.success('Epidemiology Extraction Model Loaded!')
         GARD_dict, max_length = extract_abs.load_GARD_diseases()
     st.success('All Models and Dependencies Loaded!')
+'''
 
+#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)
+    # https://docs.streamlit.io/library/api-reference/widgets/st.number_input
+    
 # st.radio(label, options, index=0, format_func=special_internal_function, key=None, help=None, on_change=None, args=None, kwargs=None, *, disabled=False)
 # https://docs.streamlit.io/library/api-reference/widgets/st.radio
-#filtering = st.sidebar.radio("What type of filtering would you like?",('Strict', 'Lenient', 'None'))
+filtering = st.sidebar.radio("What type of filtering would you like?",('Strict', 'Lenient', 'None'))
 
-#extract_diseases = st.sidebar.checkbox("Extract Rare Diseases", value=False)
+extract_diseases = st.sidebar.checkbox("Extract Rare Diseases", value=False)
 # https://docs.streamlit.io/library/api-reference/widgets/st.checkbox
 
+with st.spinner('Loading Epidemiology Models and Dependencies...'):
+    classify_model_vars = classify_abs.init_classify_model()
+    st.success('Epidemiology Classification Model Loaded!')
+    NER_pipeline, entity_classes = extract_abs.init_NER_pipeline()
+    st.success('Epidemiology Extraction Model Loaded!')
+    GARD_dict, max_length = extract_abs.load_GARD_diseases()
+st.success('All Models and Dependencies Loaded!')
+
+'''
 #LSTM RNN Epi Classifier Model
-#with st.spinner('Loading Epidemiology Classification Model...'):
-#    classify_model_vars = classify_abs.init_classify_model()
-#st.success('Epidemiology Classification Model Loaded!')
+with st.spinner('Loading Epidemiology Classification Model...'):
+    classify_model_vars = classify_abs.init_classify_model()
+st.success('Epidemiology Classification Model Loaded!')
 
 #GARD Dictionary - For filtering and exact match disease/GARD ID identification
-#with st.spinner('Loading GARD Rare Disease Dictionary...'):
-#    GARD_dict, max_length = extract_abs.load_GARD_diseases()
-#st.success('GARD Rare Disease Dictionary Loaded!')
+with st.spinner('Loading GARD Rare Disease Dictionary...'):
+    GARD_dict, max_length = extract_abs.load_GARD_diseases()
+st.success('GARD Rare Disease Dictionary Loaded!')
 
 #BioBERT-based NER pipeline, open `entities` to see 
-#with st.spinner('Loading Epidemiology Extraction Model...'):
-#    NER_pipeline, entity_classes = extract_abs.init_NER_pipeline()
-#st.success('Epidemiology Extraction Model Loaded!')
-
+with st.spinner('Loading Epidemiology Extraction Model...'):
+    NER_pipeline, entity_classes = extract_abs.init_NER_pipeline()
+st.success('Epidemiology Extraction Model Loaded!')
+'''
 
 #filtering options are 'strict','lenient'(default), 'none'
 if text:
@@ -71,4 +85,4 @@ if text:
   st.balloons()
   #st.dataframe(data=None, width=None, height=None)
   
-# st.code(body, language="python")
+# st.code(body, language="python")