Update app.py

app.py

@@ -95,41 +95,30 @@ else:
                     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
 
-                    # Ensure that the output from TAPAS is processed for Plotly
+                    # Extract relevant values 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
-                        base_sentence = f"The average for '{question}' is {avg_value:.2f}."
-                    elif 'sum' in question.lower() or aggregator == 'SUM':
-                        total_sum = df.sum().sum()  # Calculate overall sum
-                        base_sentence = f"The sum for '{question}' is {total_sum:.2f}."
-                    elif 'max' in question.lower() or aggregator == 'MAX':
-                        max_value = df.max().max()  # Find overall max value
-                        base_sentence = f"The maximum value for '{question}' is {max_value:.2f}."
-                    elif 'min' in question.lower() or aggregator == 'MIN':
-                        min_value = df.min().min()  # Find overall min value
-                        base_sentence = f"The minimum value for '{question}' is {min_value:.2f}."
-                    elif 'count' in question.lower() or aggregator == 'COUNT':
-                        count_value = df.count().sum()  # Count all values
-                        base_sentence = f"The total count of non-null values for '{question}' is {count_value}."
-                    else:
-                        base_sentence = f"The answer from TAPAS for '{question}' is {answer}."
+                    # If TAPAS is returning a list of numbers for "average" like you mentioned
+                    if "average" in question.lower() and cells:
+                        # Assuming cells are numeric values that can be plotted in a graph
+                        plot_data = [float(cell) for cell in cells]  # Convert cells to numeric data
+
+                        # Create a DataFrame for Plotly
+                        plot_df = pd.DataFrame({ 'Index': list(range(1, len(plot_data) + 1)), 'Value': plot_data })
 
-                    # Display the final response
-                    st.markdown("<p style='font-family:sans-serif;font-size: 0.9rem;'> Final Generated Response: </p>", unsafe_allow_html=True)
-                    st.success(base_sentence)
+                        # Generate a graph using Plotly
+                        fig = px.line(plot_df, x='Index', y='Value', title=f"Graph for '{question}'")
+                        st.plotly_chart(fig, use_container_width=True)
+
+                    else:
+                        st.write(f"No data to plot for the question: '{question}'")
 
                 else:
                     # Handle graph-related questions
@@ -147,9 +136,7 @@ else:
                         if column in df.columns:
                             fig = px.line(df, x=df.index, y=column, title=f"Graph of column '{column}'")
                             st.plotly_chart(fig, use_container_width=True)
-                            st.success(f"Here is the graph of column '{column}'.")
                     
-                    # Stop further execution after generating the graph
                     st.stop()  # This halts further execution
 
             except Exception as e: