try to fix force plot

app.py

@@ -66,10 +66,10 @@ with gr.Blocks() as demo:
                 with gr.Column():
                     summary_plot = gr.Plot()
             with gr.Row():
-                with gr.Column():
-                    interaction_plot = gr.Plot()
                 with gr.Column():
                     force_plot = gr.Plot()
+                with gr.Column():
+                    interaction_plot = gr.Plot()
 
     def submit_inputs(
         age_input,
@@ -170,6 +170,16 @@ with gr.Blocks() as demo:
             feature_names=["age", "bmi", "hba1c", "glucose"],
         )
 
+        fig4 = plt.figure(figsize=(3, 3))
+        plt.title("SHAP Force Plot")
+
+        shap.force_plot(
+            explainer.expected_value[predicted_class],
+            shap_values_for_predicted_class,
+            df.iloc[0],
+            feature_names=["age", "bmi", "hba1c", "glucose"],
+        )
+
         # fig4 = plt.figure(figsize=(3, 3))
         # plt.title("SHAP Interaction Plot")
         # shap_interaction_values = explainer.shap_interaction_values(transformed_df)
@@ -179,17 +189,6 @@ with gr.Blocks() as demo:
         #     feature_names=["age", "bmi", "hba1c", "glucose"],
         # )
 
-        fig5 = plt.figure(figsize=(3, 3))
-        plt.title("SHAP Force Plot")
-        # Assuming you have the SHAP values for the predicted class of the single row df
-        shap.force_plot(
-            explainer.expected_value[predicted_class],
-            shap_values_for_predicted_class,
-            df.iloc[0],
-            feature_names=["age", "bmi", "hba1c", "glucose"],
-            matplotlib=True,
-        )
-
         ## save user's data in hopsworks
         if consent_input == True:
             user_data_fg = fs.get_or_create_feature_group(
@@ -202,7 +201,7 @@ with gr.Blocks() as demo:
             user_data_df["diabetes"] = existent_info_input
             user_data_fg.insert(user_data_df)
             print("inserted new user data to hopsworks", user_data_df)
-        return res, fig, fig2, fig3, fig5
+        return res, fig, fig2, fig3, fig4
 
     btn.click(
         submit_inputs,
@@ -214,7 +213,7 @@ with gr.Blocks() as demo:
             existent_info_input,
             consent_input,
         ],
-        outputs=[output, mean_plot, waterfall_plot, summary_plot, interaction_plot],
+        outputs=[output, mean_plot, waterfall_plot, summary_plot, force_plot],
     )
 
 demo.launch()