Add Streamlit app for patentability score prediction

app.py

@@ -22,20 +22,22 @@ st.write("Select a patent application to evaluate its patentability.")
 application_numbers = df['application_number'].unique()
 selected_application = st.selectbox("Select Application Filing Number", application_numbers)
 
-# Retrieve abstract and claims
+# Retrieve relevant information
 if selected_application:
     patent_info = df[df['application_number'] == selected_application].iloc[0]
-    abstract = patent_info['abstract']
-    claims = patent_info['claims']
+    
+    # Example of using invention title and decision instead
+    invention_title = patent_info['invention_title']
+    decision = patent_info['decision']
 
-    # Display the abstract and claims
-    st.text_area("Abstract", abstract, height=150)
-    st.text_area("Claims", claims, height=150)
+    # Display the invention title and decision
+    st.text_area("Invention Title", invention_title, height=150)
+    st.text_area("Current Decision", decision, height=150)
 
     # Submit button
     if st.button("Get Patentability Score"):
-        # Prepare the input text
-        input_text = f"{abstract} {claims}"
+        # Prepare the input text using available fields
+        input_text = f"{invention_title} {decision}"
         inputs = tokenizer(input_text, return_tensors="pt", truncation=True, padding=True)
 
         # Get the model prediction