Create app.py

app.py

@@ -0,0 +1,25 @@
+import pandas as pd
+import classify_abs
+#classify_abs is a dependency for extract_abs
+import extract_abs
+pd.set_option('display.max_colwidth', None)
+import streamlit as st
+
+#LSTM RNN Epi Classifier Model
+classify_model_vars = classify_abs.init_classify_model()
+
+#GARD Dictionary - For filtering and exact match disease/GARD ID identification
+GARD_dict, max_length = extract_abs.load_GARD_diseases()
+
+#BioBERT-based NER pipeline, open `entities` to see 
+NER_pipeline, entity_classes = extract_abs.init_NER_pipeline()
+
+#max_results is Maximum number of PubMed ID's to retrieve BEFORE filtering
+
+#filtering options are 'strict','lenient'(default), 'none'
+if text:
+  out = extract_abs.search_term_extraction(term, max_results, filtering,
+                                              NER_pipeline, entity_classes, 
+                                              extract_diseases,GARD_dict, max_length, 
+                                              classify_model_vars)
+  st.(out)