Add Streamlit app for patentability score prediction

app.py

@@ -33,13 +33,13 @@ print("Validation set columns:", val_df.columns.tolist())
 st.title("Milestone Patent 🐨")
 st.write("Select a patent application to evaluate its patentability.")
 
-# Dropdown for application filing numbers
-application_numbers = train_df['application_number'].unique()
-selected_application = st.selectbox("Select Application Filing Number", application_numbers)
+# Dropdown for patent numbers
+patent_numbers = train_df['patent_number'].unique()
+selected_patent = st.selectbox("Select Patent Number", patent_numbers)
 
 # Retrieve abstract and claims
-if selected_application:
-    patent_info = train_df[train_df['application_number'] == selected_application].iloc[0]
+if selected_patent:
+    patent_info = train_df[train_df['patent_number'] == selected_patent].iloc[0]
     abstract = patent_info['abstract']
     claims = patent_info['claims']