add prediction result with users data

app.py

@@ -86,9 +86,9 @@ with gr.Blocks() as demo:
         )
         res = model.predict(df)
         if res == [0]:
-            res = "the model prediction is: You don't have diabetes"
+            res_str = "the model prediction is: You don't have diabetes"
         elif res == [1]:
-            res = "the model prediction is: You have diabetes"
+            res_str = "the model prediction is: You have diabetes"
         mean_for_age = diabetes_df[
             (diabetes_df["diabetes"] == 0) & (diabetes_df["age"] == age_input)
         ].mean()
@@ -190,16 +190,23 @@ with gr.Blocks() as demo:
         if consent_input == "accept":
             print("user consented to save their data, now trying to save to hopsworks")
             user_data_fg = fs.get_or_create_feature_group(
-                name="user_diabetes_data",
+                name="diabetes_user_data",
                 version=1,
-                primary_key=["age", "bmi", "hba1c_level", "blood_glucose_level"],
+                primary_key=[
+                    "age",
+                    "bmi",
+                    "hba1c_level",
+                    "blood_glucose_level",
+                    "diabetes",
+                ],
                 description="Submitted user data",
             )
             user_data_df = df.copy()
             user_data_df["diabetes"] = existent_info_input
+            user_data_df["model_prediction"] = res[0]
             user_data_fg.insert(user_data_df)
             print("inserted new user data to hopsworks", user_data_df)
-        return res, fig, fig2, fig3, fig4, fig5
+        return res_str, fig, fig2, fig3, fig4, fig5
 
     btn.click(
         submit_inputs,