Update app.py

app.py

@@ -91,15 +91,23 @@ else:
                     # Process TAPAS-related questions if it's not a graph query
                     raw_answer = tqa(table=df, query=question, truncation=True)
 
-                    # Display raw answer from TAPAS
-                    st.markdown("<p style='font-family:sans-serif;font-size: 0.9rem;'> Raw Result From TAPAS: </p>", unsafe_allow_html=True)
-                    st.write(raw_answer)  # Display the raw result
+                    # Display raw answer from TAPAS on the screen
+                    st.markdown("<p style='font-family:sans-serif;font-size: 1rem;'>Raw TAPAS Answer: </p>", unsafe_allow_html=True)
+                    st.write(raw_answer)  # Display the raw TAPAS output
 
-                    answer = raw_answer['answer']
+                    # Ensure that the output from TAPAS is processed for Plotly
+                    answer = raw_answer.get('answer', '')
                     aggregator = raw_answer.get('aggregator', '')
                     coordinates = raw_answer.get('coordinates', [])
                     cells = raw_answer.get('cells', [])
 
+                    # Display relevant data from TAPAS output to be used by Plotly
+                    st.markdown("<p style='font-family:sans-serif;font-size: 1rem;'>Relevant Data for Plotly: </p>", unsafe_allow_html=True)
+                    st.write(f"Answer: {answer}")
+                    st.write(f"Aggregator: {aggregator}")
+                    st.write(f"Coordinates: {coordinates}")
+                    st.write(f"Cells: {cells}")
+
                     # Handle different aggregators
                     if 'average' in question.lower() or aggregator == 'AVG':
                         avg_value = df.mean().mean()  # Calculate overall average